WPS4157
Firm Innovation in Emerging Markets
Meghana Ayyagari Asli Demirgüç-Kunt Vojislav Maksimovic*
Abstract: In this paper we investigate the determinants of firm innovation in over 19,000
firms across 47 developing economies. We define the innovation process broadly, to
include not only core innovation such as the introduction of new products and new
technologies, but also other types of activities that promote knowledge transfers and
adapt production processes. We find that more innovative firms are large exporting firms
characterized by private ownership, highly educated managers with mid-level managerial
experience, and access to external finance. By contrast, firms that innovate less are
typically state owned firms without foreign competitors. Identity of the controlling
shareholder seems to be particularly important for core innovation - private firms whose
controlling shareholder is a financial institution are the least innovative. While the use of
external finance is associated with greater innovation by all private firms, it does not
make state owned firms more innovative. Financing from foreign banks is associated
with higher levels of innovation compared to financing from domestic banks.
Keywords: Innovation, Firm Behavior, Financing and Governance
JEL Classification: O31, D21, G32
World Bank Policy Research Working Paper 4157, March 2007
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the
exchange of ideas about development issues. An objective of the series is to get the findings out quickly,
even if the presentations are less than fully polished. The papers carry the names of the authors and should
be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely
those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors,
or the countries they represent. Policy Research Working Papers are available online at
http://econ.worldbank.org.
__________________
*Ayyagari: School of Business, George Washington University, ayyagari@gwu.edu ; Demirgüç-Kunt:
World Bank, ademirguckunt@worldbank.org ; Maksimovic: Robert H. Smith School of Business at the
University of Maryland, vmmaksimovic@rhsmith.umd.edu . The authors would like to thank the National
Science Foundation for support and L. Alan Winters and seminar participants at the World Bank
Microeconomics of Growth conference for useful discussions.
Introduction
A large literature has shown that financial development has a significant causal
impact on growth. However the channels through which finance operates are not as well
understood. While many economists have taken as given that innovation is one such
channel essential for economic growth and development,1 the finance literature is silent
on how innovation in developing countries is affected by firms' access to finance.
In this paper, we study the determinants of the rate at which firms across
developing countries innovate and adapt their organizations to meet market conditions.
Most firms in emerging markets are engaged in activities far from the technological
frontier and entrepreneurs innovate not just through original inventions but also by
adopting new means of production, new products and new forms of organization. Hence,
we define the innovation process broadly, to include not only core innovative activities
such as the introduction of new products and new technologies, but also other types of
activities that promote knowledge transfers such as signing joint ventures with foreign
partners or obtaining new licensing agreements, and other actions that adapt the
organization of the firm's business activities such as opening a new plant or outsourcing a
productive activity.
We first identify the characteristics of innovative firms and then focus on the role
of access to finance, governance, and market competition in influencing firms' ability to
innovate. Specifically, we seek to answer the following questions:
· Are certain types of firms more innovative than others? What is the impact of
firm size, age, legal status, and industry sector on the extent of innovative
activities a firm is involved in?
· How does access to external finance help innovation? Does access to finance
disproportionately benefit some firms more than others? How does the source
of external finance and collateral requirements influence firm innovation?
· Are state-owned enterprises more or less innovative than other firms? Are
private enterprises organized as corporations more innovative than other
private enterprises?
1See, for example, Schumpeter (1934), Baumol (2002) and Aghion and Durlauf (2005) on the importance
of innovation for growth and development. Schumpeter (1934) also highlights the need for thinking about
innovation more broadly than just as inventions.
2
· How does competition, both the number of competitors and the identity of the
competitor, influence innovation?
We use a sample of over 19,000 firms in 47 countries, taking measures of firm
innovation from firms' responses to a stratified random survey. The survey also reports
data on each firm's organization and ownership, the type of product market competition it
faces, the educational level of its managers and the amount and sources of external
financing.
We find that the externally financed proportion of a firm's investment
expenditures is positively related to firm innovation, even after controlling for growth
opportunities. Financing from foreign banks has a much larger impact than financing
from local banks, both in promoting core innovation of introducing new product lines and
technologies as well as other innovative activities related to opening a new plant, and
establishing foreign joint ventures and new licensing agreements. Firms are also more
innovative if a greater share of their borrowing is in a foreign currency.
Interestingly, we find that state-owned firms are an exception to these findings.
State firms that obtain external financing are not significantly more likely to innovate
(and in some cases, even less likely to innovate) than those state firms that do not obtain
external financing.
These results do not appear to be driven by reverse causality. We find that there is
a great deal of heterogeneity in the way external finance facilitates firm innovation.
Furthermore, using instrumental variable techniques to deal with the potential
endogeneity of external finance leaves the results unchanged.
Firm ownership and legal organization are also important determinants of firm
innovation. Privately owned firms are, in general, more innovative than state owned
enterprises and those organized as corporations are more innovative than firms organized
as proprietorships, partnerships or cooperatives. Identity of the controlling shareholder
seems to be particularly important for the introduction of new technology and those
private firms whose controlling shareholder is a financial institution are the least
innovative.
We also find suggestive evidence for the role of competition in spurring
innovation. Firms are more innovative if the firm is an exporting firm. Foreign
3
competition, in particular, has a positive influence on the innovation rates of firms. By
contrast, having a state-owned competitor does not have a significant effect on firm
innovation. We also find evidence that managerial education and experience, and the
education level of the workers are important determinants of firm innovation.
Our findings are most closely related to two recent papers examining the role of
finance in facilitating innovation and entrepreneurship. Using data on Italian firms,
Benfratello et al. (2006) show that local banking development has a positive effect on the
probability of a firm introducing process or product innovation and this is particularly so
for small firms and for firms in sectors more dependent on external finance. Their paper
however does not examine how access to external finance at the firm level affects
innovation. Gompers et al. (2006) on the other hand, study the supply side of capital.
Using data on venture capital financing of US firms they show that suppliers of capital
have a unique ability to identify the most skilled and successful entrepreneurs. In our
paper we examine if the firms that do get external capital are indeed more innovative than
firms that are not dependent on external finance.
The rest of the paper is organized as follows. Section 2 presents the motivation
and our hypotheses. Section 3 discusses the data and summary statistics and section 4
presents the empirical model. We discuss our main results in section 5. Section 6
concludes.
2. Motivation
2.1. Finance and Innovation
There is a large empirical literature establishing that financial development
promotes long term economic growth.2 Specifically, at the macro cross-country level,
King and Levine (1993) and Levine, Loayza, and Beck (2000) show that financial
development promotes growth. Cross-country time-series studies by Bekaert, Harvey,
and Lundblad (2001, 2005) also show that financial liberalization boosts economic
growth by improving the allocation of resources and the investment rate. Demirguc-Kunt
and Maksimovic (1998) and Rajan and Zingales (1998) provide evidence at the firm and
industry level showing that reduced access to external finance is associated with lower
2See Levine (2005) for a review.
4
growth rates. Beck, Demirguc-Kunt, and Maksimovic (2005) further show that this effect
is especially pronounced for smaller firms.
However, the channels through which access to finance affects firm growth is not
well understood. Clearly, access to external finance can facilitate capital accumulation.
However, on a macro scale, historians have identified innovation and technological
progress as the principal causes of material progress over extended periods of time (see
for example, Landes (1969), Rosenberg (1982) and Mokyr (1990)). Solow's (1957) path
breaking analysis of growth in labor productivity in the U.S. has established that
technological advances (broadly defined) and skill, rather than capital accumulation are
the prime drivers of increases in labor productivity. Solow (1957) argues that
approximately 80% of the increase in labor productivity in the U.S. over the period 1909-
1949 was due to more productive use of capital and increases in the skill level of the
labor force. More recently, Levine, Loayza, and Beck (2000) have shown that financial
sector development helps economic growth through more efficient resource allocation
rather than through increases in the scale of investment or savings mobilization.
Given the importance of technological advances for growth, it is important to ask
whether financial development promotes growth by fostering innovation and thus
increasing efficiency. Such an effect would occur if the financial system has an
important role in supplying capital to firms that are innovating or restructuring their
operations in ways that make them more efficient.
We consider innovation, both narrowly defined as a firm's adoption of new
technology and introduction of new product lines, and a broader definition that takes into
account changes in the firm's operations such as a decision to outsource certain activities
or open a new plant.3 We investigate below whether access to external finance is
associated with greater firm innovation whereby firms adapt their operations at a higher
rate.4
3In the next section, we define the activities we analyze more precisely.
4Using UK data, Aghion, Bond, Klemm, and Marinescu (2004) find that firms that report R&D activity are
financed differently than firms that do not report any R&D activity.
5
2.2. Firm Governance and Innovation
A large literature in finance has linked firm governance to firm value, share price
and profitability.5 However, none of these papers have explored the role of firm
governance in promoting innovation. We explore how four aspects of firm governance
relate to innovation. First, we examine whether innovation rates differ between private
businesses and state enterprises, two ownership structures with very different incentive
mechanisms. The work of Shleifer (1998) and La Porta, Lopez-de-Silanes, and Shleifer
(2002) on the performance differences between state and privately owned firms, suggests
that the rate of innovation should be significantly higher in private businesses.
Second, we examine whether the organizational form of private businesses affects
their innovation. Demirguc-Kunt, Love, and Maksimovic's (2006) investigation of the
incorporation decision suggests that corporations become more prevalent and have
comparatively higher growth rates in better institutional environments. However, we do
not know if the differences in organizational forms, with their concomitant differences in
governance, affect the rate of innovation.
Third, we also examine if the identity of the controlling shareholder of a private
business affects its innovation. Recent work by Raphael and Villalonga (2006) suggests
that family controlled firms may be systematically different from other businesses.
Family ownership is likely to be particularly important in developing countries where the
protection of minority shareholders is limited. Hence, we investigate whether the identity
of the controlling shareholder is correlated with the rate of innovation.
Fourth, we examine how educational attainment, prior work experience, and
tenure of the firm's top management relate to the rate of innovation. A negative relation
between tenure in top management and firm innovation might suggest managerial
entrenchment and be indicative of governance or contracting problems which prevent
efficient turnover.
5The studies linking governance to firm performance include Black (2001), Black, Jang and Kim (2006),
Durnev and Kim (2005), Klapper and Love (2004), Gompers, Ishii and Metrick (2003), Lang, Lins, and
Miller (2003), and Doidge, Karolyi, and Stulz (2004). Most of these studies are based on large firms and do
not include small and medium firms that dominate our study.
6
2.3. Competition and Innovation
We also examine the relation between firm innovation and the intensity of
competition in the product market. The effect of the product market on firm innovation is
of particular policy interest, since it is likely to be easier to control the amount of
competition and the openness of the product market to foreign competition, than to
reform a country's legal and financial institutions. Some support for this view is provided
by Blundell, Griffith, and Van Reenan (1995), who find that in developed economies, as
concentration and monopoly power increases, the rate of innovation falls. Nickell (1996)
and Nickell, Nicolitsas, and Dryden (1997) find an inverse relation between growth in
productivity and industry concentration. More recently, Aghion et al. (2006) have shown
that intensity of competition, as measured by entry into an industry, affects efficient and
inefficient incumbent firms differently. Entry spurs innovation among the more
technologically advanced incumbent firms and slows it among the less efficient
incumbents.
We measure the number of competitors a firm faces, their relative technological
sophistication, and the quality of competition. In our sample, firm organization and
governance are likely to be important predictors of efficiency. Thus, we track domestic
private competitors, foreign competitors (who, in our developing country sample, are
likely to be more sophisticated) and competitors who are state enterprises. The latter are
likely to be poor competitors based on the findings of earlier literature.
Of particular interest is the effect of the interaction between the firm's
organizational structure and the level of competition on the rate of innovation. Allen and
Gale (2000) argue that for most firms in developing countries, the relevant disciplining
device for controlling agency costs is the intensity of competition in the product market.6
As the intensity of competition increases, a firm's freedom to deviate from efficient
investment and innovation policies declines. A counter argument would suggest that as
the level of competition increases, the firm's ability to enter into beneficial implicit
contracts with customers and suppliers may decrease because the value of maintaining a
6See also Scharfstein (1988), Alchian (1950), Stigler (1958) and Hart (1983).
7
reputation also decreases.7 Below, we explore the relation between competition,
governance, and firm innovation.
Finally, we also consider the relation between firm size and innovation. Since
Schumpeter (1947), there exists a large literature relating the rate of innovation to firm
size in developed economies.8 Below, we explore differences in the rate of innovation
across firm size categories in our sample of developing country firms. We also treat firm
size as a control variable in our tests of the relation between financial access and
governance and the rate of innovation.
In summary, the literature on firm growth and financial development suggests that
innovation is likely to be an important channel through which financial development
affects growth. Below we test this hypothesis by examining the relationship between
firm innovation and external financing, firm governance and product market competition.
In our sample, the governance factors that are likely to be important are ownership
structure and differences in legal organization, and their interaction with product market
competition.
3. Data and Summary Statistics
The World Bank Investment Climate Survey database (ICS) consists of firm
survey responses of over 19,000 firms in 47 developing countries.9 The core survey uses
standardized survey instruments and a uniform sampling methodology to benchmark the
investment climate of individual economies across the world and to conduct firm
performance analyses. The survey also report detailed information on firm employment,
age, industry, ownership, legal status, and the number of establishments. The Investment
Climate Survey sample from the universe of registered businesses and follow a stratified
random sampling methodology. 10
7See, for example, Maksimovic (1988) or Maksimovic and Titman (1991).
8According to Schumpeter, large firm size is essential for innovation since larger firms can provide
economies of scale in production and innovation. Other studies, by contrast, have emphasized the role of
small firms including Rothwell and Dodgson, 1994; Acs and Audretsch (1987); and Scherer (1965) to
name a few.
9The survey actually covers 44,000 firms in 67 countries. The sample is reduced to 19813 firms in 47
countries after eliminating observations with missing firm-level innovation variables.
10A detailed description of the sample design and sample frame can be found at
http://www.enterprisesurveys.org/documents/Sampling_Note.pdf and a detailed description of the
8
A great advantage of this survey is its broad coverage of the extent of innovation
that the firms undertake. Previously, there has been very little consistent data across
countries on the nature of innovative activities undertaken by firms. Moreover, the
available data typically covers only the developed countries and focuses on patents and
R&D expenditures. However, the issues are likely to be different for most developing
countries where imitation and adaptation of already-created and tested innovations, rather
than cutting-edge innovations, are likely to be more important. Thus, in studying
innovation in developing countries, it is all the more important to define innovation
broadly rather than just as new inventions.
The new investment climate surveys allow us to capture the rate of firm
innovation in this broader sense. Specifically, the surveys ask firms if they have
undertaken any of the following ten innovative activities in the last three years:
Developed a major new product line, Upgraded an existing product line, Introduced new
technology that has substantially changed the way that the main product is produced,
Discontinued at least one product (not production) line, Opened a new plant, Closed at
least one existing plant or outlet, Agreed to a new joint venture with a foreign partner,
Obtained a new licensing agreement, Outsourced a major production activity that was
previously conducted in-house, and Brought in-house a major production activity that
was previously outsourced. The firm responses are coded as 0-1 (No-Yes) dummy
variables for each of the 10 questions.
In addition to the ten individual indicators of firm innovation, we analyze three
aggregate indicators for each firm as reported in panel B of Table 1. Our approach
parallels La Porta et al's (1998) use of indices that aggregate individual characteristics in
the study of corporate governance. INDEX8 is an aggregate index obtained by summing
the number of activities in which the firm engages, excluding two of the activities,
Discontinued at least one product line and Closed at least one existing plant or outlet.11
These activities are left out of INDEX8 because they are less likely to require outside
financing than activities such as the introduction of new technology or the opening of a
implementation can be found at
http://www.enterprisesurveys.org/documents/Implementation_note_January_2007.pdf
11We also experimented with an aggregate indicator of the ten individual indicators of innovation as well
as a principal component indicator of the ten individual indicators of innovation and found our results to be
consistent with the aggregate index, INDEX8.
9
plant. They are instead represented in INDEX2 which is obtained by summing firm
responses to the two activities, Discontinued at least one product line and Closed at least
one existing plant or outlet. CORE is an aggregate index obtained by summing firm
responses to two activities, Developed a major new product line, and Introduced new
technology that has substantially changed the way that the main product is produced, to
reflect the narrow definition of core innovation as used in existing literature.12
In addition to the rich detail on the innovative activities undertaken by firms, the
survey has information on firm size, age, legal organization, number of establishments
and capacity utilization, all of which are used as firm level controls in our study. The
survey defines firms of different sizes, small, medium and large firms, on the basis of the
number of full time workers.13 Small firms are defined as those with less than 20
employees, medium firms employ 20 to 99 employees, and the large firms employ 100 or
more employees. The sample is largely dominated by small and medium sized firms.
Small firms make up 37% of the sample, medium firms constitute 35%, and large firms
constitute 28% of the overall sample. Thus, the survey provides data across a much
broader cross-section of firm sizes than is available in commercial data bases, such as
Worldscope.
Table 1 summarizes the proportion of firms in each country that undertook each
of the ten innovative activities over the year prior to the survey. All the countries in the
sample are developing economies with GDP per capita in 2000 ranging from 192 U.S.
dollars in the case of Tanzania to 11,646 U.S. dollars in the case of Slovenia.
The countries in the sample show a great deal of variation across the ten different
categories of firm innovation. Firms in any country are more likely to undertake only
certain types of innovative activities than others and hence in no single country are firms
uniformly less or more innovative across the 10 different categories. Nevertheless, the
aggregate indices, INDEX8 and CORE2, suggest that firms from Cambodia, Brazil, and
South Africa are the most innovative, while firms from Egypt, Oman, and Turkey are the
12In unreported regressions we also analyzed a core innovation index which includes upgrading an existing
product line. While the results were unchanged in majority of the specifications, we prefer to leave this
index out of the core innovation index as it may overestimate the extent of innovation, since even very
minor changes may qualify as upgrades.
13Employment is typically the most reliable figure in developing countries. Hence, number of full time
workers is used as a measure of firm size by the World Bank Group and other international survey teams
including RPED and the Oxford Centre for the Study of African Economies.
10
least innovative. For instance, 68% of Brazilian firms introduced a new product line,
95% upgraded an existing product line and another 68% introduced a new technology
compared to Egyptian firms that were the least active in each of these categories (with
corresponding numbers of 15%, 23% and 11% respectively). However, it is important to
note that Brazilian firms are not innovative across all categories. Only 4% of Brazilian
firms sign joint ventures and only 7% enter into new licensing agreements (the numbers
for Egypt, Oman, and Turkey are similar) compared to 23% of firms in Belarus that sign
new joint ventures and 38% of Russian firms that enter into new licensing agreements.
When we look at the numbers across different firm size groups, we find that
larger firms are more innovative across all activities compared to smaller firms. The
aggregate indicators also reveal that larger firms are more innovative than smaller firms.
Table 2 contains the sample statistics of the variables we consider. It shows that
across countries, a higher percentage of firms are more actively engaged in core
innovation (42% introduced new product lines and 39% introduced new technology) than
in other types of innovative activities (for instance, only 7% signed joint ventures). The
aggregate indicator, INDEX8, shows that firms on average undertake around two out of
eight activities.
The firms in the survey are broadly classified in terms of legal organization into
corporations; cooperatives, sole proprietorships and partnerships; and all other forms.
Corporation is a legal status dummy that takes the value one if the firm is organized as a
Corporation and 0 if the firm is organized as a Cooperative, Sole Proprietorship or
Partnership or has some other form. Panel A of Table 2 shows that 43% of the sample is
composed of corporations. The average firm age in the sample is 16 years. The survey
also asks firms to report the number of separate operating facilities or establishments.
While most firms are single establishment firms (73%), the mean number of separate
operating facilities is about two establishments per firm.
The growth opportunities available to a firm may be an important determinant of
the extent and type of innovative activities a firm is engaged in. Since we do not have a
direct measure of a firm's growth opportunities, we use firms' capacity utilization rates as
a proxy for growth opportunities of the firm. In the survey, capacity utilization is defined
as the amount of output actually produced relative to the maximum amount that could be
11
produced with the firm's existing machinery, equipment and regular shifts. We include
dummy variables to identify firms that have low growth opportunities (capacity
utilizations below 50%), medium level of growth opportunities (capacity utilization
between 50 and 80%) and firms with high growth opportunities (capacity utilization rates
in excess of 80%). The variable Capacity Utilization takes on values 1 to 3 corresponding
to the three categories just identified. When we look at the individual capacity utilization
dummies (summary statistics not reported in the table), we find that more than 50% of the
firms in the sample have high capacity utilization rates, indicating high growth
opportunities.
Panel B of Table 2 presents the correlations between the different innovation
indicators and Panel C presents the correlations between the aggregate innovation
indicators and firm level variables. Panel B shows that all aspects of firm innovation are
highly correlated at the 1% level. The correlation coefficients range from 0.03 to about
0.46. The highest correlation coefficient of 0.46 indicates that firms that introduce a new
product line are also highly likely to upgrade an existing product line. Panel C of Table 2
shows that the aggregate indicators CORE2 and INDEX8 are very highly correlated with
each other, with a correlation coefficient of 0.81 and are also significantly correlated with
INDEX2 and all other firm variables. However, given the correlations among different
firm characteristics, we investigate these relations in the next section through regression
analysis.
4. Determinants of Firm Innovation: The Empirical Model
To study determinants of firm innovation we proceed in two steps. First, we
analyze innovative activities controlling for broad firm characteristics, such as size, age,
legal status, number of establishments, industry and capacity utilization. We also control
for the GDP/Capita of the country. Next, we introduce variables that enable us to
examine the relationships between innovation and firm financing, governance, and
competition environment. We do not include all variables at once so as to not overload
the specification and to avoid reducing the sample size significantly since some of these
variables are available for only a subset of observations.
12
In the first step, the regression equations we estimate are of the form:
Firm Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4
Corporation Dummy +5 Number of Establishments + 6 Capacity Utilization Dummies
+ 7 Industry Dummies + 8 Country Dummies + (1)
All regressions are estimated using firm level data across 47 countries.14 The
dependent variable is either one of the three aggregate indicators (INDEX8, CORE, or
INDEX2), or one of the ten underlying indicators of innovation based on firms' responses
to survey questions. Since the ten individual indicators of firm innovation are 0-1
variables, these regressions are estimated using a Logit probability model. For the
aggregate indicators, we use Ordered Logit. All regressions report robust standard errors.
We use equation (1) as the baseline and build on it to examine the impact of
governance (i.e. competition, ownership, management) and access to external finance. In
the second step the regression equations we estimate are of the form:
Firm Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4
Corporation Dummy +5 Number of Establishments + 6 Capacity Utilization Dummies
+ 7 Industry Dummies + 8 Country Dummies + 9 X + (2)
where X is a variable or a vector of variables characterizing different aspects of the firm's
financing, governance, and competition environment.
5. Results
Table 3 reports the estimated coefficients of baseline regression (1). The table
shows that individual firm characteristics are an important determinant of the extent of
innovation a firm undertakes. Probability of undertaking all types of innovative activities
increases with firm size. Compared to small firms, medium and large firms are more
likely to develop new product lines, upgrade existing product lines, introduce new
technology, discontinue at least one product, open a new plant, close at least one existing
plant, sign a new joint venture with a foreign partner, sign new licensing agreements,
outsource a major activity and bring in-house a previously outsourced activity. The F-test
14We prefer to include country dummies in the regression specification rather than clustering since
clustering would assume the country effect to be a part of the composite error term and thus uncorrelated
with the other regressors. However, we find that the amount of external financing varies significantly
across countries necessitating the use of country dummies.
13
reported in Table 3 suggests that the differences between medium and large firms are
significant. Larger firms are also more innovative when we look at the aggregate
indicators. The marginal effects (not shown in the table) calculated for the most
innovative (CORE=2) firms show that the probability of core innovation increases by
16% for large firms compared to smaller firms. 15
The number of establishments increases the probability that a firm will open or
close a plant, as expected. Firms with a larger number of establishments are also more
likely to sign new joint ventures and outsource a major activity and are more innovative
based on the aggregate indicators as well.
Controlling for size and the number of establishments, firms organized as
corporations also report more innovative activity than other businesses. The marginal
effects show that the probability of core innovation increases by 3.7% for incorporated
firms compared to cooperatives, sole proprietorships or partnerships.16 Being
incorporated has no effect on plant opening and closing decisions, although it increases
the probability of all other activities.
Looking at the aggregate indicators, we also find evidence that younger firms and
firms with higher growth opportunities are more innovative. These effects are also
economically significant. For instance, the marginal effects of Core Innovation with
respect to capacity utilization and age reveal that with a unit change in growth
opportunities (high capacity utilization), the probability of core innovation increases by
7.5% and with a unit change in age, the probability of core innovation decreases by -
0.08%.
The underlying innovation indicators suggest more diversity. For instance,
younger firms are more likely to introduce new products and new technology, upgrade
existing product lines, open a new plant, sign joint ventures, and bring in previously out-
sourced activities, but older firms are more likely to discontinue products or close
15The marginal effects are computed at the mean of the other independent variables and are not reported in
the tables. Throughout the paper, discussion of marginal effects refers to the case where marginal effects
are computed for Core Innovation=2.
16Since the model is nonlinear, the value of predicted probabilities depends on the values of all other
control variables. The economic effects reported are evaluated at the mean value of the control variables.
However, even when we estimate the predicted probabilities for corporates and non-corporates for the full
distribution of the control values, we see that the corporations have consistently higher predicted
probabilities of innovation than un-incorporated firms.
14
existing plants. Growth opportunities do not affect a firm's out-sourcing/in-sourcing
decisions or likelihood of opening a new plant or signing new licensing agreements. On
the other hand, firms with high growth opportunities are less likely to discontinue
products and close plants.
All industries are not equally innovative as suggested by the F-tests reported at
the foot of the table. Although not reported in the table, our results indicate that of the 26
industries that the firms in our sample belong to, those in electronics, metals and
machinery, chemicals and pharmaceuticals, telecommunications, auto and auto
components, and other manufacturing are the most innovative in this sample of countries.
Table 3 also shows that for this sample of countries, there is contrasting evidence
on the effect of average GDP/Capita of the country on core innovation versus the other
types of innovative activities a firm undertakes. The coefficient of Log GDP/Capita is
negative and significant only in the case of firms introducing new product lines, but is
positive and significant for firm discontinuing products, opening and closing plants,
signing joint ventures and licensing agreements and outsourcing production activities.
5.1. External Financing and Innovation
In this section, we examine whether the availability of external finance affects the
extent of innovation that a firm undertakes. In the Investment Climate Assessments
surveys, enterprise managers were asked: "Please identify the contribution over the last
year of each of the following sources of financing for your establishment's new
investments that includes new land, buildings, machinery and equipment." The sources
are internal funds or retained earnings, local commercial banks (loan, overdraft), foreign
owned commercial banks, leasing arrangement, investment funds, trade credit, credit
cards, equity, funds from family and friends, informal sources, such as moneylenders, and
other sources. The sum of these proportions adds up to one hundred percent. The survey
also asks firms if they have a bank loan and the year in which the financing was approved.
Hence we construct a Bank Loan dummy which takes the value 1 if the firm had been
approved for a bank loan in 2001 or earlier and 0 if the firm did not have a bank loan
approved prior to 2002. The Bank Loan dummy measures past access to external
financing.
15
We also examine the impact of the share of borrowing in foreign currency and the
necessity of collateral. The share of borrowing in foreign currency is the borrowing
denominated in foreign currency as a share of total borrowing. The necessity of collateral
is a dummy variable that takes the value one if financing requires collateral or a deposit,
and zero otherwise.
The results in Table 4 show that there exists a significant positive relation
between the use of external finance and the extent of firm innovation. In particular,
external financing from foreign banks, leasing, investment funds and trade credit are
significantly positively related (at the 1% level) to the aggregate innovation indices,
INDEX8 and CORE. The underlying indicators reveal that foreign bank financing is
important for all types of innovative activities except discontinuing products, closing
plants and sourcing agreements. On the other hand, trade credit financing is particularly
important for sourcing arrangements. The F-tests testing the difference between local and
foreign banks show that financing from foreign banks is associated with significantly
higher rates of innovation compared to financing from local domestic banks especially in
the case of introducing new technology, opening new plants and signing new joint
ventures. This difference is also significant for the aggregate index, INDEX8. When we
examine the effect of access to bank financing in the past on innovation, we find that the
Bank Loan dummy coefficient is positive and significant for all the aggregate indices.
We also find that firm innovation increases with greater share of borrowing in
foreign currency. Demirguc-Kunt and Maksimovic (1998), Rajan and Zingales (1998)
and Beck, Demirguc-Kunt, and Maksimovic (2005) show that access to external finance
is associated with higher firm growth rates. These papers do not specify the channels by
which access to finance affects firm growth. Our results show that in developing
economies access to external financing and, in particular, foreign financing, is associated
with a higher rate of innovation.
5.2 Governance and Innovation: The Impact of Ownership, Competition, and
Management
In this section, we examine the impact a firm's governance structure has on its
innovation. First, we look at the impact of firm ownership, whether it is private or state-
16
owned; and for private firms, the impact of the identity of the controlling shareholder.
Second, we analyze the firms' competition environment. And finally, we investigate the
impact of human capital, i.e. the education and experience level of firm managers, as well
as that of workers.
Ownership Structure: The role of private versus public ownership has been a
much researched area in finance and has been particularly relevant in developing
countries, many of which opted for state ownership of the "strategic" sectors as a way of
achieving their development goals. However, there has been little empirical evidence on
the impact of public versus private ownership on firm innovation. In this section we
examine if being a private owned firm versus a state owned firm, or a domestic versus a
foreign owned firm has any impact on firm innovation. State (Domestic) ownership is a
dummy variable that takes the value 1 if the state (domestic private sector) owns 50% or
more of the company and 0 otherwise.
We also break down domestic private ownership into the following seven
categories - Individual, Family, Financial Institution, Managers, Employees, Domestic
Corporation and Others. These are dummy variables that take the value 1 if the largest
shareholder or owner in the firm is an individual, family, financial institution, manager of
the firm, employee of the firm, domestic company, or someone other than one of these
categories including the government or government agencies.17 Recent evidence in
finance on the role of family firms has been mixed. Several papers posit that family
owned and managed firms are better able to mitigate owner-manager agency problems
and hence are more valuable (eg: Palia and Ravid (2002), Adams, et al. (2004),
Fahlenbrach (2004)) and that founders bring valuable skills to the firm (Morck et al.
(2000)). Burkart, Panunzi, and Shleifer (2003) however argue that hired professionals
may be better managers than family founders or their heirs and the decision to cede
control to professional management depends on the investor protection environment. In
more recent work, Raphael and Villalonga (2006) show that whether family firms are
more valuable or not depends closely on management (eg: Founder-CEO or Founder
17In our sample construction for the regressions, we first test state owned firms against all other private
sector firms (both domestic and foreign). For our regressions with the domestic dummy, we drop all firms
with greater than 50% state ownership and test domestic versus foreign ownership. Finally, we drop all
firms with greater than 50% foreign ownership and investigate how the identity of the firm owner impacts
innovation in a sample of domestic private sector firms.
17
Chairman with outside CEO) and the presence/absence of control enhancing features.
While we don't have data on management and controlling structures in family firms, we
are able to separately study the importance of both family firms and management skills
on innovation.
We find that state ownership has a negative impact on overall firm innovation.
State owned firms are less likely to introduce new products, upgrade existing products,
introduce new technology, open new plants, or sign new joint ventures or licensing
agreements than privately owned firms. When we compare domestic versus foreign
ownership, we see that domestic firms are more likely to close existing plants or bring in-
house previously outsourced activities whereas foreign ownership increases the
probability that a firm will sign new joint ventures with foreign partners and new
licensing agreements.
Next, we investigate whether the actual identity of the domestic private
controlling shareholder makes a difference for firm innovation. At the 1% and 5%
significance level, identity of the controlling shareholder seems to be particularly
important for introduction of new products, new technology, discontinuing products,
opening new plants, and signing joint ventures and licensing agreements. Private firms
whose controlling shareholder is a financial institution tend to be less innovative in
particular. This is of interest since firms owned by financial institutions presumably have
easier access to finance, yet are less innovative, suggesting that when finance is not
provided on market criteria, the effect can be counter-productive. We also find that
employee owned firms and firms owned by domestic corporations are more likely to
discontinue products.
When we look at the aggregate indicators of firm innovation, we find that if the
controlling shareholder is an individual or a family or the manager of the firm, firms are
more innovative than if the largest shareholder is the government. Firms owned by a
financial institution or investment fund are particularly less innovative than other types of
ownership structures. This is consistent with La Porta, Lopez-de-Silanes and Zamarripa
(2003) who find that related loans, where banks lend to firms controlled by the bank's
owners, are not necessarily to the best firms. They find that 33% of related loans are more
likely to default and have lower recovery rates than unrelated loans. Looking at the
18
aggregate innovation indices, CORE and INDEX8, the F-test rejects that all coefficients
are equal to each other.
Competition: We use seven variables to study different aspects of firm
competition: Number of competitors; Percentage of sales sold domestically, that helps
identify whether a firm is an exporter or not; Firm's technology compared to competitor,
that takes values 1, 2 or 3 depending on whether the technology is less advanced, about
the same or more advanced than that of its main competitor; Does the firm have a foreign
competitor is a dummy variable that takes the value 1 if the firm has one or more foreign
firms as a competitor; Does the firm have a state competitor is a dummy variable that
takes the value 1 if the firm has one or more state owned enterprises as a competitor and
0 if the firm has no state competitors; Foreign Competition has greatest influence to
reduce production costs is a dummy variable that takes the value 1 if foreign competition
had the greatest influence to reduce production costs and takes the value 0 if the greatest
influence was from domestic competition, customers, creditors, shareholders or the
government instead; and Foreign Competition had greatest influence to develop new
products is a dummy variable that takes the value 1 if foreign competition was the most
important influence on the firm to develop new products and takes the value 0 if the
greatest influence was from domestic competition, customers, creditors, shareholders or
government instead.
The results in Table 6 suggest that the higher the number of competitors, the more
likely that the firm will bring in house previously outsourced activities, and less likely
that the firm will open new plants or enter into new licensing agreements. There is also
some evidence that higher the number of competitors, the firm is also more likely to
engage in core innovation though these results are not statistically significant. Firms with
a greater percentage of their sales sold domestically rather than exported are overall not
as innovative as exporting firms, suggesting that non-exporters face lesser competitive
pressures than exporting firms. Exporters are more likely to upgrade product lines,
introduce new technology, open new plants and enter into joint ventures or licensing
agreements. If the firm's technology is better than that of its competitor, the firm is more
likely to engage in all types of innovative activities except discontinuing product lines
and closing plants.
19
Table 6 also shows that the identity of the competitor can be important.18 Facing
competition pressures from a foreign owned firm is beneficial for all types of innovative
activities except opening plants and signing new licensing agreements. The aggregate
indicators, CORE and INDEX8 are also positive and significant indicating the positive
influence of foreign competition on core innovation. Interestingly, having one or more
state owned firms as a competitor has no significant effect on the aggregate indicators of
firm innovation. When we look at the individual indicators, a firm is less likely to
discontinue products if it faces state competition.
Given the positive influence of foreign competition,19 we further investigate if the
influence of foreign competition works through its impact on firms' decisions to develop
new products or reduce production costs. Firms reporting that foreign competition had
the greatest influence to reduce their production costs were more likely to introduce new
products, open new plants, sign new joint ventures and licensing agreements. Firms
reporting that foreign competition had the greatest influence to develop new products
were most likely to sign new joint ventures with foreign partners. Interestingly,
differentiation strategies rather than cost reduction strategies had a greater impact on firm
sourcing decisions.
Managerial Education and Experience - Impact of Human Capital: Next, we
examine if a firm's human capital has an important influence on innovation capability.
Human capital, as measured by the education and experience level of the management
and workforce, has been shown to have an important influence on firm investment
decisions and overall firm behavior. In this section we examine the influence of human
capital on a firm's rate of innovation. We specifically look at the education and
experience level of the top manager and the workforce.
The variables are defined as follows: Top Manager's Total Years of Experience is
the total number of years of experience the top manager has had working in this sector,
before running the establishment; Mid-Level Experience is a dummy variable that takes
the value 1 if the top manager has had between 3-10 years of experience working in this
18The variables capturing the identity of the competitor (foreign or state) and the influence of foreign
competition are available for a much smaller sample of firms. Sample sizes in these regressions range from
4300-4900 firms.
19In unreported regressions, we also find that percentage of foreign competition has an impact on the
aggregate indicators.
20
sector before running the establishment; Highly experienced is a dummy variable that
takes the value 1 if the top manager has had more than 10 years of experience working in
this sector before running the establishment; Skilled Foreign workers is the percentage of
permanent skilled workers that are foreign nationals; Percentage of workforce that has
more than 12 years of education summarizes the percentage of workforce with formal
university level education of 12 years or more; and Highest education level of the
manager takes values 1 to 6 according to the following categories-did not complete
secondary school, completed secondary school, vocational training, some university
training, graduate degree and post graduate degree.
We find that the number of years of prior experience the top manager has had in
the same industry has no effect on whether the firm is likely to be innovative or not. On
investigating deeper, we find that firms run by managers with three to ten years of
experience are more innovative than firms run by inexperienced managers. Specifically
these firms are more likely to introduce new product lines, upgrade existing product lines,
introduce new technology and sign new licensing agreements. Managerial experience of
more than 10 years seems to be important mainly in the case of bringing in-house
previously outsourced activities.
When we look at the importance of skill we find some evidence that foreign
skilled workers are an asset when it comes to signing a new joint venture with a foreign
partner. The education level of both the manager and the workforce, have a significant
influence on the extent of innovation a firm undertakes. We find that firms with
workforce with greater than twelve years of education are more innovative along most
dimensions, except with respect to opening and closing plants and bringing in-house
previously outsourced activities. However, having a highly educated manager makes a
firm more innovative along all dimensions.20 These results support the importance of
human capital as measured by education and experience level of managers and workers
for firm innovation.
20On the education question, firms were asked to report what percent of workforce had the following
education levels: Less than 6 years ("some elementary"), 6-9 years, 10-12 years, More than 12 years (some
university) with the four values summing to a 100%. Dropping firms that had values greater than or less
than 100 did not change any of the results.
21
5.3. External Financing, Competition, and Innovation-Robustness
5.3.1. External Financing and Innovation
The results in Table 4 suggest a strong correlation between firm innovation and
external finance. While this may indicate that the availability of external finance spurs
firm innovation, it could also suggest reverse causality. Firms that innovate and therefore
have better growth opportunities may also be the ones that are able to raise external
finance and introduce new technologies and products.
To control for reverse causation, we control for growth opportunities in our
regressions by including a variable "capacity utilization" at the firm level. Even after
controlling for growth opportunities, firm size (employees and number of establishments),
age, industry and legal organization, external financing is strongly related to firms'
probability to undertake core innovation, and other innovative activities. In addition, we
find that access to bank financing in years before the survey (prior to 2002) also has a
positive and significant impact on firm innovation suggesting that our results are not
driven by reverse causality. Nevertheless, in this section we probe deeper into the
relationship between firm innovation and external finance. First, we estimate
instrumental variable regressions to deal with reverse causality more formally and second,
we investigate if external finance affects all firms' innovation rates in the same way.
In Panel A of Table 8, we use two stage instrumental variable (IV) regressions to
deal with the potential endogeneity. The regressions control for baseline firm
characteristics and the instrumented external finance variable. In the first stage we use
three sets of instruments for external finance. First, we use historical variables
commonly used in the literature, namely Latitude of a country's capital city, the country's
Legal Origin, Religion, and Ethnic Diversity. These are found to be highly correlated
with the development of financial systems around the world.21 Second, since our analysis
is at the firm level as opposed to pure cross-country, we also use external financing
averaged within each country. While innovation at an individual firm may lead to greater
external finance for that firm, it is not likely that it would explain the average level of
external financing in that country. All instruments are significantly correlated with firm
21See Beck, Demirguc-Kunt, and Levine (2003) and Ayyagari, Demirguc-Kunt, and Maksimovic (2006,
2007) for a discussion of these different instruments.
22
level external finance. Finally, we use historical instruments again but do all the analysis
at the country level. The aggregate innovation indicators (dependent variables) and
external financing (independent variable) are averaged across countries. In the last
specification, since we are performing the analysis at the country level, we only control
for Log GDP/capita and do not control for any of the firm level variables (age, firm size,
number of establishments, capacity utilization, industry or legal form).
Since the IV approach is applicable only to linear models, in panel B, we also
report two stage regressions. In the first stage, ordinary least squares regressions are used
to predict external financing. In the second stage, to investigate the impact of the
predicted value of external financing on innovation, we use ordered logit regressions.
Panel A shows that the coefficient of the instrumented external financing variable
is positive and significant in the CORE and INDEX8 regressions, suggesting that reverse
causality is not the main driver of our findings. External financing does not have an effect
on discontinuing products or closing plants as shown in the INDEX2 regressions. These
results are reinforced when we look at the two stage results in Panel B. The predicted
value of external financing from first stage regressions has a positive and significant
impact on core innovation.
Next, we explore if access to external finance benefits all firms universally by
interacting external finance with firm size, age, ownership and organizational form in
Table 9. Table 9 shows that while the availability of external finance makes firms more
likely to innovate regardless of age and legal organizational form, ownership does matter.
We have some evidence that state firms are likely to innovate less with external finance
(see INDEX8) compared to private firms. Foreign firms, on the other hand, are likely to
innovate more with external finance compared to private domestic firms, particularly by
introducing new technology and through obtaining new licensing agreements. The
aggregate innovation indices also indicate that foreign firms are more innovative with
external financing.
There is some evidence that large enterprises are more likely to introduce new
technology and sign new licensing agreements with greater access to external finance.
23
External financing doesn't seem to particularly help innovation in small and medium
enterprises.22
However, it could be that we are unable to capture the differences by treating
firms of different sizes together in the same regression. Small sample sizes prevent us
from running separate regressions for each size group. Hence, to further analyze the link
between firm size and innovation, in Figure 1, we compute the average sources of
external financing used by different firms. We sub-categorize the firm sizes into Small0,
Small1, Small2, Medium0, Medium1, Medium2, Large0, Large1, and Large2 to reflect
the extent of core innovation the firms undertake. For instance, Small0 reflects small
firms that undertake no core innovation, Small1 reflects firms that undertake take at least
one core innovative activity (i.e. introduce new products or introduce new technology)
and Small2 reflects firms that undertake both types of core innovation.
Figure 1 shows that both small and large firms that innovate (Small2 and Large2
respectively) use a greater amount of external financing (or lesser amount of internal
financing) than small and large firms that do not innovate (Small0 and Large0
respectively). This pattern is particularly pronounced for small firms. Several other
interesting patterns are revealed in the types of financing that firms use. On comparing
just the innovators, Small2, Medium2 and Large2, we find that small firms that innovate
rely mostly on financing from family and friends for their external financing needs where
as medium and large firms rely mainly on bank financing.
Together, Table 9 and Figure 1 suggest that there is more than simple reverse
causality since not all firms that receive external finance are equally innovative. Thus,
although external finance is important in enabling firms to implement innovations, some
firms are better able to make use of this financing.23
5.3.2. Competition and Innovation
In this section we investigate if there are non-linearities in the impact of
competition and external financing on innovation. Recent work by Aghion et al. (2006)
22In unreported regressions, we find that the interaction term of external financing and a small firm dummy
is significant at the 1% level for bringing in-house previously outsourced activities.
23In unreported regressions we have also investigated whether availability of finance affects all industries
equally. Again there are differences, with IT Services, Metals and Machinery, and Mining and Quarrying
industries innovating more with greater external finance.
24
predicts an inverted U relationship between competition and innovation, in the sense that,
innovation initially increases with an increase in product market competition and then
declines. The inverted U relationship is particularly applicable to core innovation in
countries and industries that are at the forefront of the technology frontier.
In our sample of emerging markets, where innovation is mainly through
adaptation or imitation, we examine if there are non-linearities in the relation between
competition and innovation by interacting with firm characteristics. We are particularly
interested in the interaction between firm organization and competition on innovation.
While we used seven indicators of competition in Table 6, in this section, we restrict
ourselves to the variable which is available for the largest sample of firms - Percentage of
establishment sales that are sold domestically.
In Table 10, we present interaction regressions with the full set of control
variables. The aggregate indicators in Table 10 show that while there is an inverse
relationship between the percentage of establishment sales sold domestically and the
extent of innovation, this is less likely when the firm is a corporation and more likely
when the firm has 50% or more state ownership or is a small/medium sized firm. When
we interact percentage of sales sold domestically with other firm characteristics such as
age and foreign ownership, we find that none of these firm characteristics have a
significant influence on the extent of innovation of exporters versus non-exporters as
shown by the aggregate indicators
The underlying indicators reveal some differences however. Exporters who are
older are more likely to sign joint ventures with foreign partners and those that are
foreign owned are more likely to sign joint ventures as well as open new plants.
While the above results show that competition has a significant impact on
innovation and varies according to the types of firms, we recognize that inclusion of
industry and country dummies may not be sufficient to remove all spurious correlation
between competition and the innovation indicators. In the absence of time series data and
information on policy reforms across our sample of countries that might have allowed us
to correct for the potential endogeneity in the competition measure, we leave the
identification issues in this area for future work.
25
6. Conclusions
The strong and independent causal role of finance in promoting growth has been
demonstrated in recent literature using quantitative evidence from around the world. A
large body of empirical work has also demonstrated the importance of good governance
ownership structures and market competition for value creation by firms.
Understanding how an effective financial system contributes to economic
development and which characteristics of the business environment promote good
governance is crucial to optimize policy recommendations to help develop financial
sectors that promote growth. Since innovation responses to a changing economic
environment are widely considered to be the main driver of the growth process,
understanding the links between finance and firm innovation is an important step in
identifying the channels through which financial development contributes to economic
development.
Using firm level data for over 19,000 firms in 47 developing countries, this paper
provides evidence that a firm's access to finance is an important determinant of the extent
of innovation it undertakes. We define innovation broadly, to include not only core
innovation activities (introducing new technology, new product lines and upgrading
them), but also other types of activities that promote knowledge transfers (such as signing
joint ventures with foreign partners and obtaining new licensing agreements), as well as
opening or closing plants, discontinuing product lines, and activity sourcing decisions,
which reflect the overall dynamism of firms.
Our results indicate that the more innovative firms are younger but larger, and are
exporting firms characterized by private ownership, highly educated managers with mid-
level managerial experience, and access to external finance. By contrast, firms that do not
innovate much are typically state owned firms who do not have foreign competitors.
Identity of the controlling shareholder seems to be particularly important for the
introduction of new technology and those private firms whose controlling shareholder is a
financial institution, tend to be the least innovative. We find evidence that the use of
external finance is associated with greater innovation by foreign firms, yet state owned
firms with external financing are even less innovative. Financing from foreign banks is
associated with higher levels of innovation compared to financing from domestic banks
26
and innovation also increases with a greater share of the firm's borrowing in foreign
currency.
The findings of this paper are consistent with the well-established result in the
literature that financial development and institutions that are associated with good
governance lead to economic growth. In this paper, we provide additional evidence at the
micro level by showing that one of the channels through which access to finance affects
the growth process is through spurring firm innovation. We also find suggestive
evidence that higher competition and good governance are associated with greater
innovation.
27
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Schumpeter, Joseph A., 1947, Capitalism, Socialism, and Democracy, (Harper Brothers,
New York)
Shleifer, Andrei, 1998, State versus Private Ownership, Journal of Economic
Perspectives 12, 133-150.
Solow, Robert M., 1957, Technical Change and the Aggregate Production Function,
Review of Economics and Statistics 39 (August), pp. 312-320.
Stigler, George, 1958, The economies of scale, Journal of Law and Economics 1, 54-71.
31
Table 1: Indicators of Firm Innovation
This table presents the proportion of firms in each country undertaking different types of innovations. The variables are described as follows: GDP per capita is real GDP per capita in US dollars in
2000. Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product is produced, Discontinued at
least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing agreement,
Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsourced are all dummy variables that take the
value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the firm has undertaken any of the ten different innovative
activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by adding 1 if the firm has Discontinued at least one product
(not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if the firm has Developed a new product line or Introduced a
new technology. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have above 100 employees.
Upgrad Disco Brought
ed ntinue New in-house a
existin d at Closed at JV Outsou previously
New g New least 1 least one with New rced a out-
GDP/ product product Techno produ Opened a existing foreign Licensing major sourced
Nation Capita line line logy ct new plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Albania 1007.95 0.43 0.45 0.33 0.11 0.02 0.04 0.05 0.05 0.04 0.12 0.75 1.47 0.15
Armenia 629.91 0.31 0.42 0.26 0.19 0.04 0.05 0.09 0.13 0.11 0.10 0.56 1.44 0.24
Azerbaijan 533.48 0.31 0.31 0.22 0.14 0.06 0.08 0.09 0.32 0.06 0.04 0.54 1.42 0.22
Belarus 1896.41 0.44 0.62 0.33 0.17 0.06 0.07 0.23 0.37 0.21 0.14 0.77 2.41 0.24
Bhutan 532.21 0.59
Bosnia and Herzegovina 1594.60 0.39 0.61 0.33 0.11 0.16 0.09 0.16 0.09 0.07 0.06 0.70 1.82 0.20
Brazil 4626.34 0.68 0.95 0.68 0.41 0.16 0.08 0.04 0.07 0.28 0.21 1.35 3.06 0.50
Bulgaria 1544.94 0.57 0.54 0.31 0.30 0.14 0.10 0.06 0.26 0.04 0.10 0.88 2.01 0.40
Cambodia 367.51 0.53 0.90 0.60 0.05 0.18 0.02 0.21 0.21 0.33 0.41 1.14 3.38 0.07
China 824.63 0.24 0.40 0.33 0.57
Croatia 5077.08 0.51 0.74 0.37 0.30 0.27 0.16 0.09 0.13 0.05 0.13 0.86 2.25 0.44
Czech Republic 5380.49 0.28 0.48 0.23 0.16 0.28 0.13 0.06 0.08 0.05 0.14 0.51 1.61 0.29
Ecuador 1705.06 0.52 0.84 0.51 0.44 0.06 0.09 0.11 0.08 0.20 0.10 1.03 2.42 0.53
Egypt, Arab Rep. 1216.65 0.15 0.23 0.11 0.15 0.02 0.01 0.04 0.25
El Salvador 1759.68 0.62 0.82 0.51 0.43 0.06 0.08 0.09 0.04 0.11 0.08 1.13 2.33 0.51
Estonia 3792.29 0.29 0.51 0.32 0.22 0.22 0.22 0.05 0.21 0.12 0.06 0.61 1.76 0.44
Georgia 768.13 0.33 0.44 0.29 0.28 0.14 0.06 0.06 0.13 0.04 0.08 0.62 1.51 0.34
Guatemala 1562.57 0.53 0.82 0.43 0.39 0.08 0.16 0.12 0.04 0.13 0.14 0.96 2.29 0.55
Honduras 713.11 0.47 0.72 0.46 0.31 0.07 0.09 0.09 0.04 0.08 0.09 0.92 2.03 0.40
Hungary 5439.15 0.24 0.35 0.15 0.22 0.20 0.16 0.04 0.08 0.14 0.09 0.39 1.29 0.37
Indonesia 1014.63 0.38 0.68 0.22 0.22 0.07 0.08 0.06 0.08 0.13 0.10 0.58 1.65 0.29
Kazakhstan 1547.98 0.34 0.43 0.19 0.19 0.05 0.16 0.06 0.27 0.06 0.03 0.52 1.43 0.34
Kyrgyz Republic 443.96 0.41 0.54 0.30 0.23 0.11 0.15 0.12 0.20 0.08 0.04 0.71 1.77 0.37
Latvia 2608.12 0.37 0.56 0.33 0.26 0.23 0.17 0.05 0.26 0.05 0.03 0.69 1.86 0.43
32
Upgrad Disco Brought
ed ntinue New in-house a
existin d at Closed at JV Outsou previously
New g New least 1 least one with New rced a out-
GDP/ product product Techno produ Opened a existing foreign Licensing major sourced
Nation Capita line line logy ct new plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Lithuania 2617.61 0.49 0.40 0.29 0.31 0.09 0.09 0.07 0.19 0.16 0.06 0.76 1.70 0.38
Macedonia, FYR 2541.06 0.35 0.40 0.32 0.09 0.15 0.04 0.21 0.08 0.22 0.08 0.67 1.80 0.12
Mali 292.81 0.46 0.59 0.50 0.11 0.11 0.06 0.06 0.05 0.06 0.07 0.94 1.85 0.17
Moldova 424.47 0.51 0.59 0.30 0.34 0.28 0.18 0.07 0.29 0.07 0.14 0.81 2.25 0.52
Nicaragua 502.65 0.47 0.85 0.53 0.37 0.05 0.11 0.09 0.02 0.10 0.08 1.00 2.19 0.48
Oman 5921.12 0.36 0.46 0.32 0.14 0.21 0.05 0.04 0.07 0.04 0.08 0.20 0.46 0.06
Philippines 1173.14 0.49 0.64 0.42 0.42 0.13 0.11 0.06 0.13 0.21 0.14 0.88 2.14 0.51
Poland 4337.37 0.43 0.56 0.27 0.18 0.08 0.08 0.01 0.09 0.02 0.02 0.70 1.48 0.25
Romania 1461.46 0.47 0.70 0.31 0.18 0.31 0.15 0.06 0.21 0.07 0.22 0.78 2.35 0.33
Russian Federation 2944.13 0.39 0.50 0.30 0.27 0.12 0.15 0.04 0.38 0.08 0.01 0.68 1.77 0.42
Serbia and Montenegro 1631.59 0.38 0.58 0.36 0.08 0.26 0.12 0.17 0.11 0.07 0.10 0.72 2.01 0.20
Slovak Republic 4303.32 0.33 0.77 0.34 0.27 0.24 0.18 0.05 0.17 0.06 0.09 0.67 2.04 0.45
Slovenia 11646.10 0.28 0.41 0.33 0.20 0.12 0.13 0.17 0.19 0.14 0.13 0.61 1.77 0.32
South Africa 4022.63 0.68 0.84 0.61 0.44 0.20 0.11 0.09 0.10 0.20 0.34 1.28 3.06 0.55
Syrian Arab Republic 792.82 0.42 0.46 0.33 0.21 0.04 0.06 0.74
Tajikistan 229.49 0.41 0.55 0.35 0.33 0.03 0.14 0.06 0.18 0.06 0.04 0.76 1.67 0.46
Tanzania 191.75 0.33 0.58 0.32 0.18 0.11 0.07 0.04 0.09 0.05 0.09 0.63 1.57 0.24
Thailand 2827.62 0.50 0.71 0.52 0.19 0.08 0.02 0.04 0.11 0.18 0.11 1.02 2.23 0.21
Turkey 3047.65 0.18 0.27 0.15 0.07 0.06 0.04 0.04 0.03 0.05 0.04 0.33 0.81 0.10
Uganda 348.64 0.47
Ukraine 880.88 0.45 0.57 0.37 0.18 0.10 0.08 0.19 0.19 0.10 0.11 0.83 2.10 0.26
Uzbekistan 654.31 0.28 0.44 0.22 0.16 0.06 0.11 0.05 0.19 0.06 0.05 0.50 1.35 0.27
Zambia 403.82 0.49 0.69 0.50 0.27 0.34 0.14 0.06 0.06 0.11 0.17 0.99 2.41 0.41
Small (1-19) 0.33 0.49 0.28 0.19 0.08 0.07 0.05 0.10 0.08 0.09 0.59 1.61 0.27
Medium (20-99) 0.44 0.63 0.40 0.27 0.12 0.09 0.06 0.11 0.15 0.14 0.82 2.17 0.36
Large (100 and over) 0.51 0.70 0.50 0.32 0.18 0.12 0.12 0.16 0.18 0.15 0.99 2.60 0.44
33
Table 2: Summary Statistics
Panel A presents the summary statistics, Panel B presents the correlation matrix between the firm innovation variables and Panel C between the aggregate innovation variables and firm level variables.
The variables are described as follows: Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product
is produced, Discontinued at least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new
licensing agreement, Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsourced are all dummy
variables that take the value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the firm has undertaken any of the ten
different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by adding 1 if the firm has Discontinued
at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if the firm has Developed a new product
line or Introduced a new technology. Log GDP/capita is the logarithm of GDP per capita in 2000. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have
above 100 employees. Firm age is the year of the survey (2000)-year established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a dummy variable
that takes the value 1 if the firm is legally incorporated and 0 if the firm is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization takes values 1 to 3
corresponding to capacity utilization levels below 50%, between 50% and 80% and above 80%.
Panel A: Summary Statistics
Standard
Variable N Mean Deviation Minimum Maximum
Individual Innovation Indicators
New product line 19031 0.42 0.5 0 1
Upgraded existing product line 19028 0.6 0.49 0 1
New Technology 19417 0.39 0.49 0 1
Discontinued at least 1 product 16644 0.26 0.44 0 1
Opened a new plant 15121 0.13 0.33 0 1
Closed at least one existing plant 15111 0.09 0.29 0 1
New JV with foreign partner 16638 0.07 0.26 0 1
New Licensing Agreement 16647 0.12 0.32 0 1
Outsourced a major activity 16093 0.13 0.34 0 1
Brought in-house a previously out-sourced activity 15127 0.13 0.33 0 1
Aggregate Innovation Indicators
CORE 19415 0.79 0.81 0 2
INDEX8 15478 2.08 1.68 0 8
INDEX2 15478 0.35 0.57 0 2
Control Variables
Log (GDP/Capita) 47 7.3 0.87 5.26 9.36
Firm Size 19684 1.91 0.8 1 3
Age 19760 16.55 16.31 0 202
Number of Establishments 15314 2.05 5.89 0 200
Corporations 18963 0.43 0.49 0 1
Capacity Utilization 17982 2.4 0.67 1 3
34
Panel B: Correlation Matrix between the Firm Innovation Indicators
Closed at
Upgraded Discontinued least one New JV New Outsourced
New existing New at least 1 Opened a existing with foreign Licensing a major
product line product line Technology product new plant plant partner Agreement activity
Upgraded existing product line 0.4612a
New Technology 0.3787a 0.4424a
Discontinued at least 1 product 0.2777a 0.2297a 0.2004a
Opened a new plant 0.1678a 0.1186a 0.1485a 0.0960a
Closed at least one existing plant 0.0491a 0.0366a 0.0315b 0.2003a 0.2148a
New JV with foreign partner 0.1366a 0.1112a 0.1177a 0.0623a 0.1340a 0.0976a
New Licensing Agreement 0.1281a 0.0827a 0.1066a 0.0749a 0.1595a 0.1080a 0.2229a
Outsourced a major activity 0.1672a 0.1735a 0.1882a 0.1305a 0.1151a 0.0881a 0.1509a 0.1267a
Brought in-house a previously out-
sourced activity 0.1746a 0.1699a 0.1832a 0.1117a 0.1292a 0.0764a 0.1114a 0.0966a 0.2946a
a b
, , and represent significance at 1%, 5% and 10% respectively
c
Panel C: Correlation Matrix between the Aggregate Innovation/Innovation Indicators and the Firm Level Variables
Number of
INDEX8 CORE INDEX2 LGCAP Size Age Establishments Corporations
CORE 0.8116a
INDEX2 0.3168a 0.2612a
LGCAP 0.0145c 0.0717a 0.0326a
Size 0.2405a 0.1967a 0.1236a 0.0711a
Age 0.0513a 0.0340a 0.1177a 0.0604a 0.2767a
Number of Establishments 0.0477a 0.0185b 0.0562a 0.0280a 0.1354a 0.0764a
Corporations 0.2089a 0.2025a 0.0776a 0.1982a 0.2555a 0.0148b 0.0102
Capacity Utilization 0.0172b 0.0605a -0.0726a 0.1689a 0.0937a -0.0563a 0.0378a 0.0295a
a b
, , and represent significance at 1%, 5% and 10% respectively
c
35
Table 3: Determinants of Firm Innovation
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies + 7
Industry Dummies + 8 Country Dummies + . The variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of the following variables:
Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product is produced, Discontinued at least one
product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing agreement, Outsourced a
major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core. Each of the first ten
innovation indicators is a dummy variable that take the value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the
firm has undertaken any of the ten different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by
adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if
the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three dummies corresponding
to small, medium, and large firms. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the survey (2000) - year
established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally incorporated and 0 if the firm
is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity utilization levels below 50%,
between 50% and 80% and above 80%. Logit regressions are used for the individual indicators (columns 1-10) and Ordered Logit regressions are used for the aggregate indices (columns 11-13). The p-
value for the joint significance test of the industry dummies and the p-values for Chi-square test of Medium Firms being the same as Large firms are also reported. Detailed variable definitions and
sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Log (GDP/Capita) -0.244b -0.015 0.014 0.306b 0.909a 0.600a 0.591a 0.602a 0.522a 0.093 -0.165c -0.055 0.319a
[0.098] [0.093] [0.097] [0.128] [0.257] [0.194] [0.173] [0.168] [0.182] [0.135] [0.088] [0.081] [0.120]
Medium 0.422a 0.427a 0.331a 0.247a 0.622a 0.360a 0.627a 0.336a 0.358a 0.424a 0.426a 0.528a 0.305a
[0.048] [0.052] [0.049] [0.054] [0.077] [0.083] [0.099] [0.073] [0.074] [0.077] [0.043] [0.041] [0.052]
Large 0.718a 0.745a 0.740a 0.490a 1.155a 0.774a 1.353a 0.773a 0.537a 0.572a 0.820a 0.995a 0.597a
[0.056] [0.062] [0.057] [0.063] [0.082] [0.091] [0.104] [0.080] [0.083] [0.086] [0.051] [0.048] [0.059]
Age -0.004a -0.003b -0.004a 0.004a -0.011a 0.006a -0.004c -0.002 -0.001 -0.006a -0.005a -0.006a 0.006a
[0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001] [0.001]
Corporation 0.156a 0.252a 0.222a 0.204a 0.102 -0.13 0.284a 0.330a 0.223a 0.198b 0.207a 0.323a 0.138b
[0.052] [0.055] [0.054] [0.060] [0.074] [0.084] [0.094] [0.075] [0.077] [0.078] [0.047] [0.044] [0.056]
Number of
establishments 0 0.003 0.003 0.004 0.022a 0.018a 0.009b 0.003 0.008b -0.007 0.002 0.010a 0.013a
[0.003] [0.004] [0.003] [0.004] [0.004] [0.003] [0.004] [0.004] [0.004] [0.006] [0.003] [0.003] [0.003]
Capacity Utilization
between [50%, 80%] 0.238a 0.286a 0.342a -0.034 -0.079 -0.236b 0.03 0.139 -0.064 0.032 0.314a 0.198a -0.131c
[0.073] [0.078] [0.075] [0.078] [0.116] [0.114] [0.134] [0.118] [0.106] [0.113] [0.066] [0.063] [0.076]
36
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Capacity
Utilization>=80% 0.331a 0.295a 0.447a -0.274a -0.025 -0.565a -0.221c 0.087 -0.03 0.032 0.417a 0.229a -0.383a
[0.072] [0.077] [0.075] [0.079] [0.115] [0.115] [0.134] [0.117] [0.106] [0.113] [0.066] [0.063] [0.076]
Constant 1.265 -0.141 -1.104 -3.858a -10.951a -7.376a -7.301a -8.278a -6.963a -2.839b
[0.808] [0.781] [0.814] [1.098] [2.341] [1.731] [1.548] [1.511] [1.618] [1.146]
Observations 13823 13818 13889 13817 13476 13454 13763 13791 13472 13483 13886 13541 13541
Pseudo R-square 0.0942 0.1722 0.1174 0.0912 0.1024 0.0775 0.1252 0.111 0.1012 0.1118 0.0964 0.0734 0.0713
F-Test
Medium= Large 0 0 0 0 0 0 0 0 0.0065 0 0 0 0
Joint Significance
Test of Industry
Dummies 0 0 0 0 0 0 0 0 0 0.033 0 0 0
a b
, , and represent significance at 1%, 5% and 10% respectively
c
37
Table 4: Effect of Financing on Firm Innovation
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies +7
External Financing (or Bank Loan dummy) +8 Equity +9 Local Banks +10 Foreign Banks +11 Leasing +12 Investment Funds +13 Trade Credit +14 Credit Cards +15 Family +16 Informal Sector
(eg: moneylender) +17 Other + 18 Foreign Currency Borrowing+19 Necessity of Collateral + 20 Industry Dummies + 21 Country Dummies + . The variables are described as follows: GDP per
capita is real GDP per capita in US dollars in 2000. Innovation is one of the following variables: Developed a major new product line, Upgraded an existing product line, Introduced new technology that
has substantially changed the way that the main product is produced, Discontinued at least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to
a new joint venture with foreign partner, Obtained a new licensing agreement, Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production
activity that was previously outsource, INDEX8, INDEX2 and Core. Each of the first ten innovation indicators is a dummy variable that take the value 1 if the firm undertook the corresponding
innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the firm has undertaken any of the ten different innovative activities except Discontinued at least one product
(not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing
plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm
of GDP per capita in 2000. Firm Size Dummies consist of three dummies corresponding to small, medium, and large firms. Small firms employ 1-19 employees, Medium firms have 20-99 employees,
and Large firms have above 100 employees. Age is the year of the survey (2000) - year established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a
dummy variable that takes the value 1 if the firm is legally incorporated and 0 if the firm is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization
Dummies consist of three dummies corresponding to capacity utilization levels below 50%, between 50% and 80% and above 80%. External Financing is the proportion of new investments financed
externally and is given by 100-Proportion of new investments financed through internal funds or retained earnings. Bank Loan Dummy takes the value 1 if the firm had a bank loan approved prior to
2001 and 0 if it did not have a bank loan. Local Banks, Foreign Banks, Leasing, Investment Funds, Trade Credit, Credit Cards, Equity, Family, Informal Sources and Other represent proportion of new
investments financed by local commercial banks, foreign owned commercial banks, leasing arrangements, investment funds or special development financing, supplier or customer credit, credit cards,
sale of stock, family and friends, informal sources such as moneylenders and other. Foreign Currency Borrowing is the total borrowing denominated in foreign currency and Necessity of Collateral is a
dummy variable that takes the value 1 of the financing required collateral or a deposit and 0 otherwise. Logit regressions are used for the individual indicators (columns 1-10) and Ordered Logit
regressions are used for the aggregate indices (columns 11-13). The regressions with external financing sources also present the p-values for the corresponding Chi-square test (F-tests for columns 10-
13) for testing Local Bank financing is the same as Foreign Bank financing. Detailed variable definitions and sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
External Financing 0.002a 0.002a 0 0.001c 0.003a 0.001 0.004a 0.002b 0.002b 0.001 0.001b 0.002a 0.001c
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.000] [0.001]
External Financing Sources of New Investments
Equity 0 0.004 0.001 -0.007a 0.004 -0.006 0.007c 0.003 0.009b 0.01 0.001 0.006 -0.007a
[0.003] [0.007] [0.004] [0.002] [0.003] [0.004] [0.004] [0.002] [0.004] [0.007] [0.004] [0.006] [0.003]
Local Bank 0.001 0.003 0.002 -0.003 0 -0.003 -0.001 0 0.002 0 0.002 0.002 -0.003
[0.002] [0.003] [0.002] [0.003] [0.002] [0.004] [0.003] [0.001] [0.001] [0.002] [0.002] [0.002] [0.003]
Foreign Bank 0.004c 0.007c 0.007a 0.003 0.015a 0.002 0.012a 0.007b 0.001 0.003 0.006a 0.010a 0.003
[0.002] [0.004] [0.003] [0.002] [0.002] [0.003] [0.003] [0.003] [0.003] [0.004] [0.002] [0.003] [0.002]
Leasing 0.007a 0.007a 0.005a 0.004b 0.008a 0.002 0.004c 0.002 0.001 0.002 0.006a 0.007a 0.004b
[0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.003] [0.003] [0.002] [0.004] [0.002] [0.002] [0.001]
38
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Investment Fund 0.008a 0.020a 0.008a 0 0.010a 0.003 0.001 0.005b 0.005 0.010a 0.009a 0.010a 0.001
[0.002] [0.006] [0.003] [0.001] [0.001] [0.003] [0.003] [0.002] [0.003] [0.004] [0.002] [0.002] [0.002]
Trade Credit 0.007a 0.011a 0.005a 0.003b 0.004b 0.002 0.003 -0.001 0.004a 0.005b 0.007a 0.007a 0.003c
[0.002] [0.002] [0.002] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001]
Credit Card 0.013b 0.006 -0.002 0.001 0.009c 0.002 0.010b -0.007 0.006 -0.005 0.006 0.005 0.001
[0.005] [0.006] [0.004] [0.005] [0.005] [0.005] [0.005] [0.007] [0.006] [0.007] [0.004] [0.004] [0.004]
Family 0.005c 0.007b 0.003 -0.002 0.009a 0.003c 0.003 0.001 0.007 0.007a 0.005c 0.007b 0
[0.003] [0.003] [0.002] [0.001] [0.003] [0.002] [0.003] [0.002] [0.005] [0.002] [0.003] [0.003] [0.002]
Informal 0.003 0.005 0.002 0.001 -0.001 -0.001 -0.005 0.001 -0.001 0.006 0.001 0.001 0.001
[0.003] [0.003] [0.003] [0.003] [0.004] [0.004] [0.006] [0.003] [0.003] [0.004] [0.003] [0.003] [0.003]
Other 0.001 0.002 0.001 0.001 0.002 0.003c 0.003 0.001 0.004c 0.001 0.001 0.002 0.001
[0.001] [0.002] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.003] [0.004] [0.001] [0.002] [0.002]
Bank Loan Dummy 0.055 0.196b 0.112 0.169b -0.031 0.17 0.118 0.311a 0.146c 0.137 0.103c 0.162a 0.175b
[0.069] [0.088] [0.069] [0.072] [0.104] [0.119] [0.133] [0.112] [0.085] [0.091] [0.062] [0.058] [0.068]
Necessity of
collateral -0.072 -0.045 0.092 -0.170b -0.248b -0.241b -0.151 0.076 0.180b 0.163c -0.016 -0.01 -0.201a
[0.066] [0.076] [0.067] [0.073] [0.097] [0.112] [0.124] [0.096] [0.086] [0.093] [0.060] [0.055] [0.069]
Share of borrowing
in foreign currency 0.005a 0.003a 0.001 0.003a 0.006a 0.005a 0.010a 0.005a 0.003a 0.003b 0.004a 0.005a 0.004a
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Tests of Significance
F-Test
Local Bank=Foreign
Bank 0.2367 0.4696 0.0861 0.0719 0 0.1707 0.0008 0.0114 0.7557 0.3641 0.122 0.0089 0.0716
a b
, , and represent significance at 1%, 5% and 10% respectively
c
39
Table 5: Effect of Ownership on Firm Innovation
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies +7
State Ownership +8 Domestic Company + 9 Individual+10 Family+ 11 Financial Institution +12 Managers +13Employees+14Corporation+ 15 Industry Dummies + 16 Country Dummies + . The
variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of the following variables: Developed a major new product line, Upgraded an existing
product line, Introduced new technology that has substantially changed the way that the main product is produced, Discontinued at least one product (not production) line, Opened a new plant, Closed
at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing agreement, Outsourced a major production activity that was previously conducted in-
house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core. Each of the first ten innovation indicators is a dummy variable that take the value 1
if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the firm has undertaken any of the ten different innovative activities
except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not
production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if the firm has Developed a new product line or Introduced a new
technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three dummies corresponding to small, medium, and large firms. Small firms employ 1-19
employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the survey (2000) - year established. Number of establishments is the number of
separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally incorporated and 0 if the firm is organized as a cooperative, sole proprietorship,
partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity utilization levels below 50%, between 50% and 80% and above 80%. State
Ownership is a dummy variable that takes the value 1if the state owns 50% or more of the company and 0 otherwise. Domestic Company is a dummy variable that takes the value 1 if the domestic
private sector owns more than 50%. Individual, Family, Financial Institution, Managers, Employees and Domestic Corporation are dummy variables which take the value 1 if the largest shareholder or
owner in the firm is an individual, family, bank or investment fund, manager of the firm, employees of the firm, domestic corporation or government/government agency. Logit regressions are used for
the individual indicators (columns 1-10) and Ordered Logit regressions are used for the aggregate indices (columns 11-13). Detailed variable definitions and sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
State Ownership -0.364a -0.475a -0.378a -0.126 -0.683a 0.138 -0.532a -0.453a -0.13 -0.051 -0.420a -0.545a -0.027
[0.090] [0.090] [0.094] [0.104] [0.141] [0.128] [0.159] [0.117] [0.147] [0.151] [0.082] [0.075] [0.095]
Domestic -0.082 -0.123c 0.013 -0.003 -0.043 0.260b -0.749a -0.186b -0.164c 0.155c -0.032 -0.140a 0.082
[0.063] [0.069] [0.064] [0.070] [0.083] [0.108] [0.093] [0.081] [0.086] [0.091] [0.056] [0.053] [0.066]
Identity of the Controlling Shareholder
Individual 0.084 0.142 0.276a 0.225b 0.116 0.137 0.09 -0.022 -0.039 0.247c 0.221a 0.132c 0.190c
[0.090] [0.095] [0.091] [0.110] [0.151] [0.187] [0.197] [0.136] [0.126] [0.149] [0.083] [0.078] [0.104]
Family 0.269b 0.084 0.468a 0.153 0.402b 0.146 0.369c 0.062 -0.156 0.021 0.419a 0.211b 0.142
[0.108] [0.119] [0.109] [0.127] [0.172] [0.209] [0.223] [0.169] [0.153] [0.173] [0.098] [0.092] [0.120]
Financial Institution -0.429 -0.203 -1.392a -0.042 -0.184 0.502 -0.373 -1.661b 0.454 0.885c -0.812b -0.409 0.163
[0.403] [0.397] [0.512] [0.470] [0.508] [0.510] [0.626] [0.758] [0.542] [0.495] [0.368] [0.331] [0.430]
Managers 0.273 0.396b 0.564a 0.216 0.088 0.117 0.532c 0.385c 0.196 0.292 0.503a 0.483a 0.215
[0.181] [0.193] [0.184] [0.213] [0.277] [0.319] [0.321] [0.231] [0.264] [0.269] [0.162] [0.155] [0.198]
Employees -0.156 -0.005 0.204 0.597a -0.369 0.024 -0.17 -0.072 -0.123 0.237 0.066 -0.007 0.425b
[0.191] [0.189] [0.193] [0.208] [0.317] [0.309] [0.354] [0.230] [0.307] [0.315] [0.171] [0.157] [0.197]
40
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Domestic
Corporation 0.069 0.217c 0.164 0.369a -0.025 0.312 0.504b -0.026 0.168 0.119 0.143 0.132 0.355a
[0.121] [0.130] [0.122] [0.139] [0.184] [0.217] [0.234] [0.171] [0.167] [0.187] [0.109] [0.102] [0.131]
F-Test
All Coefficients are
equal to each other 0.0205 0.3851 0.0001 0.1535 0.0119 0.7753 0.0143 0.0763 0.2344 0.1541 0.0001 0.0279 0.3287
a b
, , and represent significance at 1%, 5% and 10% respectively
c
41
Table 6: Effect of Competition on Firm Innovation
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity Utilization Dummies +7
Competition + 8 Industry Dummies + 9 Country Dummies + . The variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of the following
variables: Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product is produced, Discontinued at
least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing agreement,
Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core. Each of
the first ten innovation indicators is a dummy variable that take the value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by
adding 1 if the firm has undertaken any of the ten different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is
formed by adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by
adding 1 if the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three dummies
corresponding to small, medium, and large firms. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the survey
(2000) - year established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally incorporated
and 0 if the firm is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity utilization
levels below 50%, between 50% and 80% and above 80%. Competition is one of the following variables: Number of competitors is the total number of competitors in the domestic market that are
private domestic enterprises, state-owned enterprises or foreign-owned enterprises, Percentage of sales sold domestically is the percentage of establishment sales that are sold domestically (instead of
being exported), Firm's Technology compared to that of its competitor takes values 1, 2 or 3 depending on whether the technology is less advanced, about the same or more advanced than that of its
main competitor, Foreign Competition had greatest influence to reduce production costs and Foreign Competition had greatest influence to develop new products are dummy variables that take value 1
if foreign competition had the greatest influence on the firm to reduce production costs or develop new products respectively and 0 otherwise, Does the firm have a foreign competitor and Does the firm
have a state competitor are dummy variables that take the value 1 if over the last year, in the company's main product line, the firm had at least one foreign owned firm as a competitor or a state owned
firm as a competitor respectively. Each cell in the table corresponds to a particular regression. Logit regressions are used for the individual indicators (columns 1-10) and Ordered Logit regressions are
used for the aggregate indices (columns 11-13). Detailed variable definitions and sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Number of
competitors 0.001 0.002 0.002 -0.003 -0.018a 0 -0.007 -0.010b -0.005 0.017a 0.001 0.001 -0.001
[0.003] [0.003] [0.003] [0.003] [0.004] [0.005] [0.005] [0.004] [0.003] [0.003] [0.002] [0.002] [0.003]
Percentage of sales
sold domestically -0.001 -0.002b -0.001c 0.001 -0.002b 0 -0.015a -0.003a -0.001 -0.001 -0.001b -0.003a 0.001
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Firm's technology
compared to
competitor 0.315a 0.371a 0.492a -0.04 0.293a -0.120b 0.327a 0.249a 0.109b 0.146a 0.445a 0.415a -0.053
[0.032] [0.035] [0.033] [0.035] [0.047] [0.050] [0.059] [0.047] [0.046] [0.047] [0.029] [0.027] [0.032]
Does the firm have a
foreign competitor? 0.235a 0.298a 0.257a 0.149b -0.002 0.236c 0.384a 0.003 0.368a 0.504a 0.278a 0.377a 0.193a
[0.070] [0.083] [0.071] [0.076] [0.113] [0.128] [0.145] [0.124] [0.093] [0.098] [0.063] [0.060] [0.073]
42
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Does the firm have a
state competitor? -0.048 -0.035 -0.03 -0.407b 0.157 0.233 -0.248 -0.145 -0.255 0.127 -0.017 -0.043 .
[0.149] [0.168] [0.152] [0.166] [0.225] [0.234] [0.308] [0.271] [0.210] [0.197] [0.133] [0.123]
Foreign Competition
had greatest influence
to reduce production
costs 0.183b 0.102 0.097 0.135 0.302b 0.147 0.707a 0.445a 0.063 -0.024 0.168b 0.268a 0.142c
[0.088] [0.122] [0.088] [0.088] [0.123] [0.139] [0.139] [0.142] [0.108] [0.115] [0.079] [0.075] [0.084]
Foreign Competition
had greatest influence
to develop new
products 0.142 0.084 0.166c 0.166c 0.089 0.002 0.634a 0.113 0.212c 0.291b 0.167b 0.272a 0.128
[0.092] [0.128] [0.093] [0.092] [0.137] [0.152] [0.146] [0.159] [0.112] [0.116] [0.083] [0.078] [0.089]
a b
, , and represent significance at 1%, 5% and 10% respectively
c
43
Table 7: Effect of Human Capital on Firm Innovation
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies +7
Human Capital Indicator + 8 Industry Dummies + 9 Country Dummies + . The variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of
the following variables: Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product is produced,
Discontinued at least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing
agreement, Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core.
Each of the first ten innovation indicators is a dummy variable that take the value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed
by adding 1 if the firm has undertaken any of the ten different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet.
INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is
formed by adding 1 if the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three
dummies corresponding to small, medium, and large firms. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the
survey (2000) - year established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally
incorporated and 0 if the firm is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity
utilization levels below 50%, between 50% and 80% and above 80%. Human Capital Indicator is one of the following variables: Top Manager's Total Years of Experience is the total number of years of
experience the top manager has had in working in this sector before running the establishment; Mid-Level Experience is a dummy variable that takes the value 1 if the top manager has had between 3-10
years of experience working in this sector before running the establishment; Highly experienced is a dummy variable that takes the value 1 if the top manager has had more than 10 years of experience
working in this sector before running the establishment; Skilled Foreign workers is the percentage of permanent skilled workers that are foreign nationals; Highest education level of the manager takes
values 1 to 6 according to the following categories-did not complete secondary school, secondary school, vocational training, some university training, graduate degree and post graduate degree;
Percentage of workforce with more than 12 years of education is the percentage of workforce at the establishment that has attended university or higher and had more than 12 years of education. Each
cell in the table corresponds to a particular regression. Logit regressions are used for the individual indicators (columns 1-10) and Ordered Logit regressions are used for the aggregate indices (columns
11-13). Detailed variable definitions and sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Top Mgr's total years
of experience 0.002 0.002 0.004 0 0 -0.005 0.004 0.003 0 0.006 0.003 0.001 0
[0.003] [0.003] [0.003] [0.003] [0.004] [0.005] [0.006] [0.005] [0.004] [0.004] [0.003] [0.002] [0.003]
Mid-level experience 0.123c 0.293a 0.160b -0.009 0.119 0.112 0.207 0.249c 0.115 0.11 0.158b 0.191a 0.006
[0.071] [0.089] [0.072] [0.075] [0.113] [0.128] [0.158] [0.129] [0.092] [0.103] [0.065] [0.061] [0.074]
Highly experienced 0.098 0.121c 0.103c -0.006 0.042 -0.125 0.227c 0.131 0.019 0.242a 0.098c 0.103b -0.032
[0.060] [0.074] [0.060] [0.062] [0.094] [0.111] [0.129] [0.111] [0.078] [0.083] [0.054] [0.052] [0.061]
Skilled foreign
workers 0.003 -0.001 0.004 0.002 0.002 -0.005 0.009c -0.004 0.006 -0.008 0.003 0.003 -0.002
[0.003] [0.004] [0.003] [0.004] [0.004] [0.006] [0.005] [0.005] [0.004] [0.005] [0.003] [0.003] [0.004]
% workforce with
>12 yrs years
education 0.005a 0.003a 0.003a 0.003a 0 -0.001 0.015a 0.006a 0.005a 0.002 0.004a 0.006a 0.002b
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
44
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Highest level of
education of manager 0.111a 0.083a 0.052a 0.047a 0.080a 0.092a 0.267a 0.134a 0.110a 0.038c 0.090a 0.111a 0.058a
[0.015] [0.017] [0.016] [0.017] [0.023] [0.026] [0.035] [0.026] [0.022] [0.022] [0.014] [0.013] [0.016]
a b
, , and represent significance at 1%, 5% and 10% respectively
c
45
Table 8: Effect of Financing on Firm Innovation ­ Addressing Reverse Causality
Panel A reports instrumental variable regressions while Panel B reports two stage regressions. The first stage regression is External Financing = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3
Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies + 7 Industry Dummies + 8 Country Dummies + 9 Historical Variables (Latitude, Ethnic ,Common Law,
Catholic, Muslim, Protest) OR Average Value of External Financing. The second stage regression in both panels is INDEX8/INDEX2/CORE= + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3
Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies + 7 Industry Dummies + 8 (Predicted Value of External Financing from the First Stage) + 9 Country
Dummies. The second stage regression is estimated using ordinary least squares in Panel A and using ordered logit in Panel B. The variables are described as follows: INDEX8 is an aggregate measure
that is formed by adding 1 if the firm has undertaken any of the ten different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or
outlet. INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation
that is formed by adding 1 if the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Small firms employ 1-19
employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the survey (2000) - year established. Number of establishments is the number of
separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally incorporated and 0 if the firm is organized as a cooperative, sole proprietorship,
partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity utilization levels below 50%, between 50% and 80% and above 80%. External
Financing is the proportion of new investments financed externally and is given by 100-Proportion of new investments financed through internal funds or retained earnings. In columns 1-3, historical
variables are used as instruments. English Common Law is a dummy variable that takes the value 1 for Common Law Countries, Catholic, Muslim and Protest are dummy variables that take the value 1
depending on whether the dominant religious group in the country are Catholics, Protestants, or Muslims respectively, Ethnic Fractionalization is the probability that two randomly selected individuals
in a country do not belong to the same ethnic group. Latitude is the absolute value of the latitude of the country scaled between zero and one. In columns 4-6, the instrument is average external financing
averaged across countries. In columns 7-9, all variables are averaged across countries. In both panels, each specification reports the adjusted R-squares from the first stage regression. Panel A also
reports the p-values of the F-test for the instruments used. Detailed variable definitions and sources are given in the appendix.
Panel A: Instrumental Variables
Average External Financing Across
Instruments Historical Variables Countries Historical Variables
1 2 3 4 5 6 7 8 9
CORE INDEX8 INDEX2
(Averaged (Averaged (Averaged
across across across
CORE INDEX8 INDEX2 CORE INDEX8 INDEX2 countries) countries) countries)
External Financing 0.006a 0.039 a 0 0.006 a 0.039 a 0
[0.002] [0.005] [0.001] [0.002] [0.005] [0.001]
External Financing 0.012 a 0.031 a 0.003
(Averaged across
countries) [0.004] [0.008] [0.002]
First Stage Adjusted R2 0.2093 0.2088 0.2088 0.209 0.2086 0.2086 0.4676 0.4004 0.4004
F-Test of Instruments 0 0 0 0 0 0 0 0 0
N 9577 9439 9439 9726 9588 9588 44 41 41
a b
, , and represent significance at 1%, 5% and 10% respectively
c
46
Panel B: Two Stage Regressions (OLS in the First Stage, Ordered Logit in the Second Stage)
Predicted Values in Average External Financing Across
Second Stage Historical Variables Countries Historical Variables
1 2 3 4 5 6 7 8 9
CORE INDEX8 INDEX2
(Averaged (Averaged (Averaged
Dependent Variable in across across across
Second Stage CORE INDEX8 INDEX2 CORE INDEX8 INDEX2 countries) countries) countries)
External Financing 0.014a 0.041 a -0.008 0.014 a 0.041 a -0.007
[0.004] [0.004] [0.007] [0.004] [0.004] [0.007]
External Financing 0.118 a 0.134 a 0.003
(Averaged across
countries) [0.029] [0.033] [0.002]
First Stage Adjusted R2 0.2093 0.2088 0.2088 0.209 0.2086 0.2086 0.4676 0.4004 0.4004
N 13688 13343 13343 13886 13541 13541 44 41 41
a b
, , and represent significance at 1%, 5% and 10% respectively
c
47
Table 9: Interaction of Financing with Firm Characteristics
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Corporations +5 Number of Establishments + 6 Capacity utilization Dummies +7
External Financing +8 External Financing X Age + 9 External Financing X Micro/Small Dummy +10 External Financing X State + 11 External Financing X Foreign + 12 External Financing X
Corporations + 13 Industry Dummies + 14 Country Dummies + . The variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of the
following variables: Developed a major new product line, Upgraded an existing product line, Introduced new technology that has substantially changed the way that the main product is produced,
Discontinued at least one product (not production) line, Opened a new plant, Closed at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing
agreement, Outsourced a major production activity that was previously conducted in-house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core.
Each of the first ten innovation indicators is a dummy variable that take the value 1 if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed
by adding 1 if the firm has undertaken any of the ten different innovative activities except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet.
INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is
formed by adding 1 if the firm has Developed a new product line or Introduced a new technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three
dummies corresponding to small, medium, and large firms. Small firms employ 1-19 employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the
survey (2000) - year established. Number of establishments is the number of separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally
incorporated and 0 if the firm is organized as a cooperative, sole proprietorship, partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity
utilization levels below 50%, between 50% and 80% and above 80%. External Financing is the proportion of new investments financed externally and is given by 100-Proportion of new investments
financed through internal funds or retained earnings. State Ownership is a dummy variable that takes the value 1if the state owns 50% or more of the company and 0 otherwise. Foreign Company is a
dummy variable that takes the value 1 if the foreign private sector owns more than 50% of the company. Logit regressions are used for the individual indicators (columns 1-10) and Ordered Logit
regressions are used for the aggregate indices (columns 11-13). Detailed variable definitions and sources are in the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Corporations 0.208a 0.181b 0.174b 0.164c 0.128 -0.125 0.22 0.363a 0.122 0.276b 0.216a 0.322a 0.096
[0.078] [0.087] [0.079] [0.089] [0.107] [0.123] [0.141] [0.111] [0.114] [0.112] [0.070] [0.066] [0.082]
External Financing 0.002b 0.002c -0.001 0.001 0.004a 0.001 0.003b 0.001 0.001 0.002c 0.001 0.002a 0.001
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
External Financing x 0 0.002 0.001 0.001 -0.001 0 0.001 0.001 0.001 -0.003c 0.001 0 0.001
Corporations [0.001] [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.001] [0.002] [0.001] [0.001] [0.001]
Age -0.002 -0.003 -0.002 0.004b -0.013a 0.009a -0.003 -0.001 0 -0.001 -0.002 0.007a -0.004a
[0.002] [0.002] [0.002] [0.002] [0.003] [0.002] [0.003] [0.003] [0.003] [0.003] [0.002] [0.002] [0.002]
External Financing 0.003a 0.002b 0 0.001 0.002b 0.002c 0.004a 0.002c 0.002c 0.002c 0.002b 0.001c 0.002a
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
External Financing x
Age 0 0 0 0 0 0 0 0 0 -0.000c 0 0 0
[0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000]
State -0.227c -0.295b -0.227c -0.036 -0.530a 0.276 -0.588b -0.238 -0.06 0.119 -0.264b -0.343a 0.115
[0.131] [0.132] [0.133] [0.153] [0.192] [0.178] [0.230] [0.166] [0.210] [0.205] [0.117] [0.109] [0.137]
48
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
External Financing 0.002a 0.002a 0 0.001 0.003a 0.002c 0.003a 0.002a 0.001c 0.001 0.001b 0.002a 0.001b
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.000] [0.001]
External Financing x -0.002 -0.003 -0.002 -0.001 -0.001 -0.007b 0.002 -0.007b 0.004 -0.004 -0.002 -0.003c -0.003
State [0.002] [0.002] [0.002] [0.003] [0.003] [0.003] [0.004] [0.003] [0.003] [0.004] [0.002] [0.002] [0.002]
Foreign -0.012 0.053 -0.308a 0 -0.08 -0.083 0.737a -0.11 0.216 0.017 -0.174b -0.013 -0.044
[0.098] [0.108] [0.101] [0.109] [0.131] [0.159] [0.147] [0.132] [0.136] [0.137] [0.087] [0.081] [0.102]
External Financing 0.002b 0.002a 0 0.001 0.003a 0.002b 0.004a 0.001 0.002b 0.001 0.001 0.002a 0.001b
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
External Financing x 0.002 0.001 0.005a 0 0.002 -0.002 0.001 0.007a -0.001 -0.003 0.004a 0.003b 0
Foreign [0.002] [0.002] [0.002] [0.002] [0.002] [0.003] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001] [0.002]
Micro/Small Dummy -0.348a -0.358a -0.314a -0.205b -0.690a -0.530a -0.788a -0.459a -0.259b -0.294a -0.366a -0.316a -0.517a
[0.076] [0.087] [0.076] [0.083] [0.100] [0.116] [0.130] [0.105] [0.103] [0.104] [0.068] [0.077] [0.064]
External Financing 0.003a 0.005a 0.002b 0.002c 0.004a 0.001 0.006a 0.004a 0.001 -0.001 0.003a 0.001 0.004a
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
External Financing x -0.001 -0.003b -0.003a -0.001 0 0.001 -0.003c -0.003c 0.001 0.002 -0.003a 0 -0.002b
Micro/Small [0.001] [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.001] [0.001] [0.001] [0.001] [0.001]
a b
, , and represent significance at 1%, 5% and 10% respectively
c
49
Table 10: Interaction of Competition with Firm Characteristics
This regression model estimated is Innovation = + 1 Log (GDP/Capita) +2 Firm Size Dummies + 3 Age + 4 Legal Status Dummies +5 Number of Establishments + 6 Capacity utilization
Dummies +7 Percentage of sales sold domestically +8 Percentage of sales sold domestically X Age + 9 Percentage of sales sold domestically X Micro/Small Dummy +10 Percentage of sales sold
domestically X State + 11 Percentage of sales sold domestically X Foreign + 12 Percentage of sales sold domestically X Corporations + 13 Industry Dummies + 14 Country Dummies + . The
variables are described as follows: GDP per capita is real GDP per capita in US dollars in 2000. Innovation is one of the following variables: Developed a major new product line, Upgraded an existing
product line, Introduced new technology that has substantially changed the way that the main product is produced, Discontinued at least one product (not production) line, Opened a new plant, Closed
at least one existing plant or outlet, Agreed to a new joint venture with foreign partner, Obtained a new licensing agreement, Outsourced a major production activity that was previously conducted in-
house and Brought in-house a major production activity that was previously outsource, INDEX8, INDEX2 and Core. Each of the first ten innovation indicators is a dummy variable that take the value 1
if the firm undertook the corresponding innovation and 0 otherwise. INDEX8 is an aggregate measure that is formed by adding 1 if the firm has undertaken any of the ten different innovative activities
except Discontinued at least one product (not production) line and Closed at least one existing plant or outlet. INDEX2 is formed by adding 1 if the firm has Discontinued at least one product (not
production) line or Closed at least one existing plant or outlet. CORE is an aggregate measure of innovation that is formed by adding 1 if the firm has Developed a new product line or Introduced a new
technology. Log (GDP/capita) is the logarithm of GDP per capita in 2000. Firm Size Dummies consist of three dummies corresponding to small, medium, and large firms. Small firms employ 1-19
employees, Medium firms have 20-99 employees, and Large firms have above 100 employees. Age is the year of the survey (2000) - year established. Number of establishments is the number of
separate operating facilities a firm has. Corporations is a dummy variable that takes the value 1 if the firm is legally incorporated and 0 if the firm is organized as a cooperative, sole proprietorship,
partnership or has another legal form. Capacity Utilization Dummies consist of three dummies corresponding to capacity utilization levels below 50%, between 50% and 80% and above 80%.
Percentage of sales sold domestically is the percentage of establishment sales that are sold in the domestic market rather than being exported. State Ownership is a dummy variable that takes the value
1if the state owns 50% or more of the company and 0 otherwise. Foreign Company is a dummy variable that takes the value 1 if the foreign private sector owns more than 50% of the company. Logit
regressions are used for the individual indicators (columns 1-10) and Ordered Logit regressions are used for the aggregate indices (columns 11-13). All Detailed variable definitions and sources are in
the appendix.
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Corporations -0.197c -0.024 0.239b -0.074 0.068 0.151 -0.344b -0.12 -0.201 -0.078 0.042 -0.052 -0.034
[0.117] [0.131] [0.119] [0.131] [0.164] [0.200] [0.168] [0.162] [0.156] [0.169] [0.106] [0.102] [0.126]
Percentage of sales
sold domestically -0.003a -0.003a -0.001 -0.001 -0.002 0.002 -0.019a -0.006a -0.005a -0.003c -0.002b -0.006a 0
[0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.001] [0.001] [0.002] [0.001] [0.001] [0.001]
Percentage of sales 0.004a 0.003b 0 0.003b 0 -0.003 0.008a 0.005a 0.005a 0.003c 0.002 0.004a 0.002
sold domestically x
Corporations [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001] [0.001]
Age -0.003 0.009b -0.001 0.006 -0.014a 0.011b -0.016a -0.007 -0.001 -0.009c -0.002 -0.004 0.009a
[0.003] [0.004] [0.003] [0.003] [0.005] [0.004] [0.005] [0.005] [0.004] [0.005] [0.003] [0.003] [0.003]
Percentage of sales
sold domestically -0.001 0.001 0 0.001 -0.003b 0.001 -0.018a -0.004a -0.001 -0.001 -0.001 -0.003a 0.002c
[0.001] [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Percentage of sales 0 -0.000a 0 0 0 0 0.000a 0 0 0 0 0 0
sold domestically x [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000]
50
1 2 3 4 5 6 7 8 9 10 11 12 13
Brought
Closed in-house a
Upgraded at least New JV previously
New existing New Discontinued Opened one with New Outsourced out-
product product Techno at least 1 a new existing foreign Licensing a major sourced
line line logy product plant plant partner Agreement activity activity CORE INDEX8 INDEX2
Age
State 0.417 0.22 0.084 0.361 -0.219 0.774b -0.328 -0.829b 0.790b 0.37 0.23 0.166 0.673b
[0.268] [0.285] [0.267] [0.287] [0.367] [0.330] [0.342] [0.370] [0.347] [0.374] [0.239] [0.238] [0.262]
Percentage of sales
sold domestically 0 -0.001 -0.001 0.001c -0.002c 0 -0.015a -0.003a -0.001 0 -0.001 -0.002a 0.002b
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Percentage of sales -0.009a -0.008b -0.005c -0.006c -0.005 -0.007b -0.002 0.005 -0.011a -0.005 -0.007a -0.008a -0.008a
sold domestically x
State [0.003] [0.003] [0.003] [0.003] [0.004] [0.004] [0.004] [0.004] [0.004] [0.004] [0.003] [0.003] [0.003]
Foreign 0.032 -0.055 0.109 0.066 -0.252 -0.398c -0.145 -0.091 -0.016 0.02 0.064 0.07 0.009
[0.122] [0.140] [0.123] [0.135] [0.166] [0.224] [0.169] [0.164] [0.154] [0.167] [0.111] [0.104] [0.130]
Percentage of sales
sold domestically 0 -0.001 0 0.002c -0.003b -0.001 -0.017a -0.004a -0.001 0 0 -0.002a 0.001c
[0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Percentage of sales 0.001 0.003 -0.001 0 0.005b 0.003 0.012a 0.004c 0.003c -0.002 0 0.001 -0.001
sold domestically x
Foreign [0.002] [0.002] [0.002] [0.002] [0.002] [0.003] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001] [0.002]
Small/Medium
Dummy -0.218c -0.280b -0.561a -0.218c -0.294c -0.582a 0.164 -0.252 0.116 0.133 -0.466a -0.349a -0.318a
[0.112] [0.125] [0.114] [0.127] [0.160] [0.205] [0.161] [0.160] [0.148] [0.161] [0.102] [0.098] [0.122]
Percentage of sales
sold domestically 0 -0.001 -0.002b 0.002 -0.001 -0.001 -0.010a -0.002c 0 0.001 -0.002c -0.002a 0.001
[0.001] [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]
Percentage of sales -0.003c -0.002 0.001 -0.002 -0.005a 0 -0.011a -0.003 -0.005a -0.005a -0.001 -0.003b -0.001
sold domestically x
Small/Medium [0.001] [0.001] [0.001] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002] [0.001] [0.001] [0.001]
51
Figure 1: Sources of External Financing Used by Firms of Different Size Groups and Innovation Types
100%
80%
Other
Informal
(%) 60% Family
Equity
Creditcard
Tradecredit
Financing
InvFund
Leasing
ernal
40% Foreign Bk
Ext Local Bk
Internal
20%
0%
Small0 Small1 Small2 Med0 Med1 Med2 Large0 Large1 Large2
Firm Size-Innovation
52
Appendix A1: Variable Definition and Sources
Variable Definition Source
Innovation Indicators
New product line Has your company developed a new product line in the last three years? Yes (1) No (0) Investment Climate Survey
Upgraded existing product line Has your company upgraded an existing product line in the last three years? Yes (1) No (0) Investment Climate Survey
Has your company introduced new technology that has substantially changed the way that the main
New Technology product is produced, in the last three years? Yes (1) No (0) Investment Climate Survey
Has your company discontinued at least one product (not production) line in the last three years? Yes (1)
Discontinued at least 1 product No (0) Investment Climate Survey
Opened a new plant Has your company opened a new plant in the last three years? Yes (1) No (0) Investment Climate Survey
Closed at least one existing plant Has your company closed at least one existing plant or outlet in the last three years? Yes (1) No (0) Investment Climate Survey
New JV with foreign partner Has your company agreed a new joint venture with a foreign partner in the last three years? Yes (1) No (0) Investment Climate Survey
New Licensing Agreement Has your company obtained a new licensing agreement in the last three years? Yes (1) No (0) Investment Climate Survey
Has your company outsourced a major production activity that was previously conducted in-house in the
Outsourced a major activity last three years? Yes (1) No (0) Investment Climate Survey
Brought in-house a previously Has your company brought in-house a major production activity that was previously outsourced in the last
out-sourced activity three years? Yes (1) No (0) Investment Climate Survey
Aggregate Innovation Indicators
An aggregate measure of firm innovation that is formed by adding 1 for each of the following cases: if the
firm has developed a new product line, upgraded an existing product line, introduced new technology,
opened a new plant, signed a new joint venture with a foreign partner, obtained a new licensing agreement,
outsourced a major production activity or brought in-house a previously outsourced activity in the past
INDEX8 three years. The Index ranges from 0 to 8 with 8 indicating the firm is most innovative. Own Calculations
An aggregate measure of firm innovation that is formed by adding 1 if the firm has discontinued at least
one product, or closed at least one existing plant. The Index ranges from 0 to 2 and is meant to capture
INDEX2 activities that do not require external financing Own Calculations
An aggregate measure of innovation that is formed by adding 1 if the firm has developed a new product
line or introduced a new technology. The Index ranges from 0 to 2 and is meant to capture activities
CORE constitute core innovation Own Calculations
Firm Size Dummies consist of three dummies corresponding to small, medium, and large firms. Small
Firm Size Dummies firms have 1-19 employees, Medium firms have20-99 employees, Large firms have over 100 employees. Investment Climate Survey
53
Variable Definition Source
Number of establishments The number of separate operating facilities of a firm. Investment Climate Survey
Age Age is the year of the survey (2000) - year established Investment Climate Survey
Corporations is a dummy variable that takes the value 1 if the firm is organized as a corporation and 0 if
Corporations the firm is organized as a Cooperative, Sole Proprietorship or Partnership or some other legal form. Investment Climate Survey
Capacity Utilization Dummies consist of three dummies corresponding to the establishment's average
capacity utilization levels below 50%, between 50% and 80% and above 80%, over the last year. Capacity
utilization is defined as the amount of output actually produced relative to the maximum amount that could
Capacity Utilization Dummies be produced with the firm's existing machinery and equipment and regular shifts. Investment Climate Survey
Competition
Number of competitors is the total number of competitors in the domestic market that are private domestic
Number of Competitors enterprises, state-owned enterprises or foreign-owned enterprises. Investment Climate Survey
Percentage of sales sold
domestically Percentage of establishment sales that are sold in the domestic market rather than being exported. Investment Climate Survey
Considering the main product line or main line of services and comparing the production process with that
of the firm's closest competitor, the following best summarizes the firm's position about its technology:
Firm's technology compared to Less advanced than that of its main competitor (1); About the same as that of its main competitor (2); More
competitor advanced than that of its main competitor Investment Climate Survey
Does the firm have a foreign Dummy variable that takes the value 1 if over the last year, in the company's main product line, the firm
competitor? had at least one foreign owned firm as a competitor. Investment Climate Survey
Does the firm have a state Dummy variable that takes the value 1 if over the last year, in the company's main product line, the firm
competitor? had at least one state owned firm as a competitor. Investment Climate Survey
Foreign Competition had greatest Dummy variable that takes value 1 if foreign competition had the greatest influence on the firm to reduce
influence to reduce production production costs of existing products and services and 0 if greatest influence instead was domestic
costs competition, customers, creditors, shareholders or government agencies. Investment Climate Survey
Foreign Competition had greatest Dummy variable that takes value 1 if foreign competition had the greatest influence on the firm to develop
influence to develop new new products or services and markets and 0 if the greatest influence was domestic competition, customers,
products creditors, shareholders or government agencies instead. Investment Climate Survey
Human Capital Investment Climate Survey
Top Mgr's total years of How many years of experience working in this sector did the top manager have before running this
experience establishment? Investment Climate Survey
Dummy variable that takes the value 1 if the top manager has had between 3-10 years of experience
Mid-level experience working in this sector before running the establishment Investment Climate Survey
Dummy variable that takes the value 1 if the top manager has had more than 10 years of experience
Highly experienced working in this sector before running the establishment Investment Climate Survey
Skilled foreign workers Percentage of permanent skilled workers that are foreign nationals Investment Climate Survey
54
Variable Definition Source
% workforce with >12 yrs years
education Percentage of workforce that has more than 12 years of education defined as university or higher. Investment Climate Survey
Highest education level of the manager takes values 1 to 6 according to the following categories-did not
Highest level of education of complete secondary school (1), secondary school (2), vocational training (3), some university training (4),
manager graduate degree (5) and post graduate degree (6) Investment Climate Survey
Ownership Investment Climate Survey
State Ownership is a dummy variable that takes the value 1if the state owns 50% or more of the company
State Ownership and 0 otherwise. Investment Climate Survey
Domestic Company is a dummy variable that takes the value 1 if the domestic private sector owns 50% or
Domestic more and takes the value 0 if the foreign private sector owns 50% or more. Investment Climate Survey
Foreign Company is a dummy variable that takes the value 1 if the foreign private sector owns 50% or
Foreign more and takes the value 0 if the domestic private sector owns 50% or more. Investment Climate Survey
Individual, Family, Financial Institution, Managers, Employees and Domestic Corporation are dummy
Identity of the Controlling variables which take the value 1 if the largest shareholder or owner in the firm is an individual, family,
Shareholder bank or investment fund, manager of the firm, employees of the firm, or domestic corporation Investment Climate Survey
External Financing Investment Climate Survey
External Financing 100-Percentage of new investment over the last year coming from internal funds or retained earnings Investment Climate Survey
Equity Percentage of new investment over the last year coming from equity, sale of stock Investment Climate Survey
Local Bank Percentage of new investment over the last year coming from local commercial banks (loan, overdraft) Investment Climate Survey
Foreign Bank Percentage of new investment over the last year coming from foreign owned commercial banks Investment Climate Survey
Leasing Percentage of new investment over the last year coming from leasing arrangement Investment Climate Survey
Percentage of new investment over the last year coming from investment funds/special development
Investment Fund financing or other state services Investment Climate Survey
Trade Credit Percentage of new investment over the last year coming from supplier or customer credit Investment Climate Survey
Credit Card Percentage of new investment over the last year coming from credit cards Investment Climate Survey
Family Percentage of new investment over the last year coming from family and friends Investment Climate Survey
Informal Percentage of new investment over the last year coming from informal sources (eg: moneylender) Investment Climate Survey
55
Variable Definition Source
Other Percentage of new investment over the last year coming from other sources Investment Climate Survey
Share of borrowing in foreign
currency Percentage share of total borrowing (loans, accounts payable) that is denominated in foreign currency? Investment Climate Survey
Necessity of collateral Did the financing require collateral or a deposit? Yes (1) No (0) Investment Climate Survey
Historical Instruments
English Common Law is a dummy variable that takes the value 1 for Common Law Countries and 0 for La Porta, Lopez-de-Silanes, Shleifer and
English Common Law Civil Law and Socialist Law Countries Vishny (1999)
La Porta, Lopez-de-Silanes, Shleifer and
Catholic Dummy Variables that takes the value 1 if the dominant religious group in the country are Catholics Vishny (1999)
La Porta, Lopez-de-Silanes, Shleifer and
Muslim Dummy Variables that takes the value 1 if the dominant religious group in the country are Muslims Vishny (1999)
La Porta, Lopez-de-Silanes, Shleifer and
Protest Dummy Variables that takes the value 1 if the dominant religious group in the country are Protestants Vishny (1999)
Ethnic Fractionalization is the probability that two randomly selected individuals in a country do not Alesina et al. (2003)
Ethnic Fractionalization belong to the same ethnic group
La Porta, Lopez-de-Silanes, Shleifer and
Latitude Latitude is the absolute value of the latitude of the country scaled between zero and one. Vishny (1999)
56